The expected upper limits on the production cross-section times the product of branching ratios for the benchmark signal scenario involving a scalar particle $X$ with narrow width decaying via $X\rightarrow aa\rightarrow 4\gamma$, $\sigma_X\times B(X\rightarrow aa)\times B(a\rightarrow\gamma\gamma)^2$. The limits for $m_{a}$ = 5 GeV and 10 GeV do not cover as large a range as the other mass points, since the region of interest is limited to $ m_{a} < 0.01 \times m_{X}$. Additionally, the expected limits are not provided for a small number of points, indicated with a hyphen, because of a technical failure with the computation.

The observed upper limits on the production cross-section times the product of branching ratios for the benchmark signal scenario involving a scalar particle $X$ with narrow width decaying via $X\rightarrow aa\rightarrow 6\pi^0$, $\sigma_X\times B(X\rightarrow aa)\times B(a\rightarrow 3\pi^0)^2$. The limits for $m_{a}$ = 5 GeV and 10 GeV do not cover as large a range as the other mass points, since the region of interest is limited to $ m_{a} < 0.01 \times m_{X}$.

The expected upper limits on the production cross-section times the product of branching ratios for the benchmark signal scenario involving a scalar particle $X$ with narrow width decaying via $X\rightarrow aa\rightarrow 6\pi^0$, $\sigma_X\times B(X\rightarrow aa)\times B(a\rightarrow 3\pi^0)^2$. The limits for $m_{a}$ = 5 GeV and 10 GeV do not cover as large a range as the other mass points, since the region of interest is limited to $ m_{a} < 0.01 \times m_{X}$. Additionally, the expected limits are not provided for a small number of points, indicated with a hyphen, because of a technical failure with the computation.

Observed 95% CL upper limits on the visible cross section as a function of $m_X$ and the fraction of events in the low-$\Delta E$ category.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.1 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.5 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.7 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 1 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 2 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 5 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 10 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 0.5 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 0.7 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 1 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 2 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 5 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 10 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.1 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.5 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.7 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 1 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 2 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 5 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 10 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 0.5 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 0.7 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 1 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 2 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 5 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 10 GeV.

Selection efficiency for photons originating from the BSM process $X\rightarrow\gamma\gamma$, where the $X$ particle is a high-mass narrow-width scalar particle originating from the gluon--gluon fusion process.

Fraction of photons with a value of shower shape variable $\Delta E$ lower than the threshold, for photons originating from the BSM process $X\rightarrow\gamma\gamma$, where the $X$ particle is a high-mass narrow-width scalar particle originating from the gluon--gluon fusion process.

1$\tau$ MediumMass SR eff.

2$\tau$ Compressed SR eff.

2$\tau$ Compressed SR eff.

2$\tau$ HighMass SR eff.

2$\tau$ HighMass SR eff.

2$\tau$ multibin SR eff.

2$\tau$ multibin SR eff.

2$\tau$ GMSB SR eff.

2$\tau$ GMSB SR eff.

1$\tau$ Compressed SR eff.

1$\tau$ Compressed SR eff.

1$\tau$ MediumMass SR eff.

1$\tau$ MediumMass SR eff.

2$\tau$ Compressed SR eff.

2$\tau$ Compressed SR eff.

2$\tau$ HighMass SR eff.

2$\tau$ HighMass SR eff.

2$\tau$ multibin SR eff.

2$\tau$ multibin SR eff.

2$\tau$ GMSB SR eff.

2$\tau$ GMSB SR eff.

1$\tau$ Compressed SR acceptance.

1$\tau$ Compressed SR acceptance.

1$\tau$ MediumMass SR acceptance.

1$\tau$ MediumMass SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ GMSB SR acceptance.

2$\tau$ GMSB SR acceptance.

1$\tau$ Compressed SR acceptance.

1$\tau$ Compressed SR acceptance.

1$\tau$ MediumMass SR acceptance.

1$\tau$ MediumMass SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ GMSB SR acceptance.

2$\tau$ GMSB SR acceptance.

Cutflow table of the $1\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $1\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $1\tau$ medium-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $1\tau$ medium-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ high-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ high-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ multibin SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ multibin SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ GMSB SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ GMSB SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Best performing fit setups entering the final combination as a function of the LSP mass and the gluino mass. 'S' marks the simultaneous fit of the four simplified model single-bin SRs, 'M' denotes the simultaneous fit of the two $1\tau$ SRs and the $2\tau$ multibin SR.

Best performing fit setups entering the final combination as a function of the LSP mass and the gluino mass. 'S' marks the simultaneous fit of the four simplified model single-bin SRs, 'M' denotes the simultaneous fit of the two $1\tau$ SRs and the $2\tau$ multibin SR.

Observed exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.

Observed exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.

Expected exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.

Expected exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.

Observed exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.

Observed exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.

Expected exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.

Expected exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.

Observed upper limits on the production cross section at 95% CL in pb as a function of tanBeta and SUSY breaking mass scale Lambda.

Observed upper limits on the production cross section at 95% CL in pb as a function of tanBeta and SUSY breaking mass scale Lambda.

Observed upper limits on the production cross section at 95% CL in pb as a function of the LSP mass and the gluino mass.

Observed upper limits on the production cross section at 95% CL in pb as a function of the LSP mass and the gluino mass.

Yields of the expected background from the SM in the bins of the multibin SR of the $2\tau$ channel with all bins being simultaneously used to constrain the background prediction. Expectation is given with the scalings computed in the combined fit applied. Uncertainties are statistial plus systematrics. Only the subsamples contributing the respective region are considered.

Yields of the expected background from the SM in the bins of the multibin SR of the $2\tau$ channel with all bins being simultaneously used to constrain the background prediction. Expectation is given with the scalings computed in the combined fit applied. Uncertainties are statistial plus systematrics. Only the subsamples contributing the respective region are considered.

$m_{\mathrm{T}}^{\tau}$ in the compressed $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau}$ in the compressed $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$E_{\mathrm{T}}^{\mathrm{miss}}$ in the compressed $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$E_{\mathrm{T}}^{\mathrm{miss}}$ in the compressed $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau}$ in the medium-mass $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau}$ in the medium-mass $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$E_{\mathrm{T}}^{\mathrm{miss}}$ in the medium-mass $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$E_{\mathrm{T}}^{\mathrm{miss}}$ in the medium-mass $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$H_{\mathrm{T}}$ in the medium-mass $H_{\mathrm{T}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$H_{\mathrm{T}}$ in the medium-mass $H_{\mathrm{T}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the top VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the top VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$H_{\mathrm{T}}$ in the $W$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$H_{\mathrm{T}}$ in the $W$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the $Z$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the $Z$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau}$ in the compressed SR of the $1\tau$ channel before application of the $m_{\mathrm{T}}^{\tau}$ > 80 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$m_{\mathrm{T}}^{\tau}$ in the compressed SR of the $1\tau$ channel before application of the $m_{\mathrm{T}}^{\tau}$ > 80 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the medium-mass SR of the $1\tau$ channel before application of the $H_{\mathrm{T}}$ > 1000 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the medium-mass SR of the $1\tau$ channel before application of the $H_{\mathrm{T}}$ > 1000 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$m_{\mathrm{T}}^{\mathrm{sum}}$ in the compressed SR of the $2\tau$ channel before application of the $m_{\mathrm{T}}^{\mathrm{sum}}$ > 1600 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$m_{\mathrm{T}}^{\mathrm{sum}}$ in the compressed SR of the $2\tau$ channel before application of the $m_{\mathrm{T}}^{\mathrm{sum}}$ > 1600 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the high-mass SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1100 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the high-mass SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1100 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

mT(tau_1) + mT(tau_2) in the multibin SR of the 2T channel. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

mT(tau_1) + mT(tau_2) in the multibin SR of the 2T channel. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the GMSB SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1900 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the GMSB SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1900 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

Expected and observed 95% CL lower limits on the mass of a vector-like $T$ quark in the branching-ratio plane.

Expected and observed 95% CL lower limits on the mass of a vector-like $B$ quark in the branching-ratio plane.

Expected and observed upper limits at the 95% CL on the $T\bar T$ cross section as a function of $T$ mass under the assumption BR($T\to Wb$)=1.

Expected and observed upper limits at the 95% CL on the $B\bar B$ cross section as a function of $B$ mass under the assumption BR($T\to Zt$)=1.

Expected and observed upper limits at the 95% CL on the $B\bar B$ cross section as a function of $B$ mass under the assumption BR($B\to Wt$)=1.

Expected and observed upper limits at the 95% CL on the $B\bar B$ cross section as a function of $B$ mass under the assumption BR($B\to Zb$)=1.

Observed and expected 95% CL upper limits on the cross-section of gluon-fusion initialted resonant production of the mass of the resonance times the branch ratio of X to HH and the BR of HH to gammagamma WW, without assuming the BR of H to gammagamma and H to WW.

Exclusion limits on higgsino pair production divided by the theory cross-section.The results of the low-mass analysis are used below m(higgsino) = 300 GeV, while those of the high-mass analysis are used above. The figure shows the observed and expected 95% upper limits on the higgsino pair production cross-section as a function of m(higgsino).

Observed and expected 95% limits in the m(higgsino) vs BR(higgsino to higgs+gravitino) plane. The regions above the lines are excluded by the analyses.

The observed and expected 95% upper limits on the total pair production cross section for degenerate higgsinos as a function of m(higgsino) for the high-mass search. Only the high-mass analysis results are used in this figure.

The observed and expected 95% upper limits on the total pair production cross section for degenerate higgsinos as a function of m(higgsino) for the high-mass search, divided by the theory cross section. Only the high-mass analysis results are used in this figure.

The observed and expected 95% upper limits on the total pair production cross section for degenerate higgsinos as a function of m(higgsino) for the low-mass search. Only the low-mass analysis results are used in this figure.

The observed and expected 95% upper limits on the total pair production cross section for degenerate higgsinos as a function of m(higgsino) for the low-mass search, divided by the theory cross section. Only the low-mass analysis results are used in this figure.

Particle-level acceptance for the low-mass discovery signal regions low-SR-MET0-meff440 and low-SR-MET150-meff440, shown as a function of higgsino mass. The acceptance is defined as the fraction of signal events passing the particle-level event selection that emulates the detector-level selection. The acceptance calculation considers only those signal events where both higgsinos decay to Higgs bosons that subsequently both decay to b-quarks.

The experimental efficiency of the low-mass analysis, for the two discovery signal regions low-SR-MET0-meff440 and low-SR-MET150-meff440, as a function of higgsino mass. The experimental efficiency is defined as the number of events passing the detector-level event selection divided by the number of events passing the event selection for a perfect detector. The denominator is obtained by implementing particle-level event selection that emulate the detector-level selection. Such particle-level selection is not applied on the numerator.

Particle-level acceptance for the high-mass discovery signal regions SR-4b-meff1-A-disc and SR-3b-meff3-A, shown as a function of higgsino mass. The acceptance is defined as the fraction of signal events passing the particle-level event selection that emulates the detector-level selection. The acceptance calculation considers only those signal events where both higgsinos decay to Higgs bosons that subsequently both decay to b-quarks.

The experimental efficiency of the high-mass analysis, for the two discovery signal regions SR-4b-meff1-A-disc and SR-3b-meff3-A, as a function of higgsino mass. The experimental efficiency is defined as the number of events passing the detector-level event selection divided by the number of events passing the event selection for a perfect detector. The denominator is obtained by implementing particle-level event selection that emulate the detector-level selection. Such particle-level selection is not applied on the numerator.

Example cutflow for SR-3b-meff3-A.

Example cutflow for SR-4b-meff1-A-disc.

Cutflow for low-mass analysis for each signal mass point.

Distributions of kinematic variables in the signal regions for the $2\ell$ channels after applying all selection requirements. The histograms show the post-fit background predictions. The last bin includes the overflow. The distribution for $R_{\textrm{ISR}}$ in SR$2\ell$_ISR is plotted. The expected distribution for a benchmark signal model, normalized to the NLO+NLL cross-section times integrated luminosity, is also shown for comparison.

Distributions of kinematic variables in the signal regions for the $3\ell$ channels after applying all selection requirements. The histograms show the post-fit background predictions. The last bin includes the overflow. The distribution for $H_{3,1}^{\textrm{PP}}$ in SR$3\ell$_Low is plotted. The expected distribution for a benchmark signal model, normalized to the NLO+NLL cross-section times integrated luminosity, is also shown for comparison.

Distributions of kinematic variables in the signal regions for the $3\ell$ channels after applying all selection requirements. The histograms show the post-fit background predictions. The last bin includes the overflow. The distribution of $p_{\textrm{T}}^{\ell_{1}}$ in SR$3\ell$_Low is plotted. The expected distribution for a benchmark signal model, normalized to the NLO+NLL cross-section times integrated luminosity, is also shown for comparison.

Distributions of kinematic variables in the signal regions for the $3\ell$ channels after applying all selection requirements. The histograms show the post-fit background predictions. The last bin includes the overflow. The distribution of $p_{\mathrm{T\ ISR}}^{~\textrm{CM}}$ in SR$3\ell$_ISR is plotted. The expected distribution for a benchmark signal model, normalized to the NLO+NLL cross-section times integrated luminosity, is also shown for comparison.

Distributions of kinematic variables in the signal regions for the $3\ell$ channels after applying all selection requirements. The histograms show the post-fit background predictions. The last bin includes the overflow. The distribution of $R_{\textrm{ISR}}$ in SR$3\ell$_ISR is plotted. The expected distribution for a benchmark signal model, normalized to the NLO+NLL cross-section times integrated luminosity, is also shown for comparison.

Expected exclusion limits at 95% CL on the masses of C1/N2 and N1 from the analysis of 36.1fb$^{-1}$ of 13 TeV $pp$ collision data obtained from the 2$\ell$ search, assuming 100\% branching ratio of the sparticles to decay to SM $W/Z$ bosons and LSP.

Observed exclusion limits at 95% CL on the masses of C1/N2 and N1 from the analysis of 36.1fb$^{-1}$ of 13 TeV $pp$ collision data obtained from the 2$\ell$ search, assuming 100% branching ratio of the sparticles to decay to SM $W/Z$ bosons and LSP.

Expected exclusion limits at 95% CL on the masses of C1/N2 and N1 from the analysis of 36.1fb$^{-1}$ of 13 TeV $pp$ collision data obtained from the the $3\ell$ search, assuming 100% branching ratio of the sparticles to decay to SM $W/Z$ bosons and LSP.

Observed exclusion limits at 95% CL on the masses of C1/N2 and N1 from the analysis of 36.1fb$^{-1}$ of 13 TeV $pp$ collision data obtained from the the $3\ell$ search, assuming 100% branching ratio of the sparticles to decay to SM $W/Z$ bosons and LSP.

Expected exclusion limits at 95% CL on the masses of C1/N2 and N1 from the analysis of 36.1fb$^{-1}$ of 13 TeV $pp$ collision data obtained from the statistical combination of the $2\ell$ and 3$\ell$ search channels, assuming 100\% branching ratio of the sparticles to decay to SM $W/Z$ bosons and LSP.

Observed exclusion limits at 95% CL on the masses of C1/N2 and N1 from the analysis of 36.1fb$^{-1}$ of 13 TeV $pp$ collision data obtained from the statistical combination of the $2\ell$ and 3$\ell$ search channels, assuming 100% branching ratio of the sparticles to decay to SM $W/Z$ bosons and LSP.

Signal region acceptance for chargino-neutralino production in SR2L_High. The acceptance is with respect to all possible $W/Z$ decays.

Signal region efficiency for chargino-neutralino production in SR2L_High.

Signal region acceptanceXefficiency for chargino-neutralino production in SR2L_High.

Signal region acceptance for chargino-neutralino production in SR2L_Int. The acceptance is with respect to all possible $W/Z$ decays.

Signal region efficiency for chargino-neutralino production in SR2L_Int.

Signal region acceptanceXefficiency for chargino-neutralino production in SR2L_Int.

Signal region acceptance for chargino-neutralino production in SR2L_Low. The acceptance is with respect to all possible $W/Z$ decays.

Signal region efficiency for chargino-neutralino production in SR2L_Low.

Signal region acceptanceXefficiency for chargino-neutralino production in SR2L_Low.

Signal region acceptance for chargino-neutralino production in SR2L_ISR. The acceptance is with respect to all possible $W/Z$ decays.

Signal region efficiency for chargino-neutralino production in SR2L_ISR.

Signal region acceptanceXefficiency for chargino-neutralino production in SR2L_ISR.

Signal region acceptance for chargino-neutralino production in SR3L_High. The acceptance is with respect to all possible $W/Z$ decays.

Signal region efficiency for chargino-neutralino production in SR3L_High.

Signal region acceptanceXefficiency for chargino-neutralino production in SR3L_High.

Signal region acceptance for chargino-neutralino production in SR3L_Int. The acceptance is with respect to all possible $W/Z$ decays.

Signal region efficiency for chargino-neutralino production in SR3L_Int.

Signal region acceptanceXefficiency for chargino-neutralino production in SR3L_Int.

Signal region acceptance for chargino-neutralino production in SR3L_Low. The acceptance is with respect to all possible $W/Z$ decays.

Signal region efficiency for chargino-neutralino production in SR3L_Low.

Signal region acceptanceXefficiency for chargino-neutralino production in SR3L_Low.

Signal region acceptance for chargino-neutralino production in SR3L_ISR. The acceptance is with respect to all possible $W/Z$ decays.

Signal region efficiency for chargino-neutralino production in SR3L_ISR.

Signal region acceptanceXefficiency for chargino-neutralino production in SR3L_ISR.

Observed 95% CL upper limit on the production cross-section of C1/N2 from the analysis of 36.1fb$^{-1}$ of 13 TeV $pp$ collision data obtained from the 2$\ell$ search, assuming 100% branching ratio of the sparticles to decay to SM $W/Z$ bosons and N1.

Observed 95% CL upper limit on the production cross-section of C1/N2 from the analysis of 36.1fb$^{-1}$ of 13 TeV $pp$ collision data obtained from the 3$\ell$ search, assuming 100% branching ratio of the sparticles to decay to SM $W/Z$ bosons and N1.

Observed 95% CL upper limit on the production cross-section of C1/N2 from the analysis of 36.1fb$^{-1}$ of 13 TeV $pp$ collision data obtained from the statistical combination of 2 and 3$\ell$ searches, assuming 100% branching ratio of the sparticles to decay to SM $W/Z$ bosons and N1.

Signal cutflow for SR2L_High and m[C1/N2,N1] = [500,0] GeV. 5000 events were generated for this point. The unweighted number of events correspond to the number of selected MC events in the produced sample, while the weighted yield is normalized to the luminosity of the data.

Signal cutflow for SR2L_Int and m[C1/N2,N1] = [400,200] GeV. 10000 events were generated for this point. The unweighted number of events correspond to the number of selected MC events in the produced sample, while the weighted yield is normalized to the luminosity of the data.

Signal cutflow for SR2L_Low and m[C1/N2,N1] = [200,100] GeV. 20000 events were generated for this point. The unweighted number of events correspond to the number of selected MC events in the produced sample, while the weighted yield is normalized to the luminosity of the data.

Signal cutflow for SR2L_ISR and m[C1/N2,N1] = [200,100] GeV. 20000 events were generated for this point. The unweighted number of events correspond to the number of selected MC events in the produced sample, while the weighted yield is normalized to the luminosity of the data.

Signal cutflow for SR3L_High and m[C1/N2,N1] = [500,0] GeV. 5000 events were generated for this point. The unweighted number of events correspond to the number of selected MC events in the produced sample, while the weighted yield is normalized to the luminosity of the data.

Signal cutflow for SR3L_Int and m[C1/N2,N1] = [400,200] GeV. 10000 events were generated for this point. The unweighted number of events correspond to the number of selected MC events in the produced sample, while the weighted yield is normalized to the luminosity of the data.

Signal cutflow for SR3L_Low and m[C1/N2,N1] = [200,100] GeV. 20000 events were generated for this point. The unweighted number of events correspond to the number of selected MC events in the produced sample, while the weighted yield is normalized to the luminosity of the data.

Signal cutflow for SR3L_ISR and m[C1/N2,N1] = [200,100] GeV. 20000 events were generated for this point. The unweighted number of events correspond to the number of selected MC events in the produced sample, while the weighted yield is normalized to the luminosity of the data.

Expected and observed upper limits at the 95% CL on the BB cross section as a function of B quark mass in the SU(2) singlet scenario.

Expected and observed 95% CL lower limits on the mass of the B quark in the branching ratio plane of BR(B->Wt) versus BR(B->Hb).

The signal selection acceptance times efficiency (A$\times \epsilon$), defined as the ratio of the number of MC signal events in the category to the number of generated signal events, is presented as a function of the HVT resonance mass in the VBF category. The A$\times \epsilon$ is shown for the combination of all decay channels. For the HVT VBF samples, generator cuts are: m$_{jj} >$ 150 GeV. The decay of $W$ and $Z$ are to all flavors of leptons. The uncertainty shown represents the total statistical and systematic uncertainties.

Signal selection acceptance times efficiency (A$\times \epsilon$), defined as the ratio of the number of MC signal events in the category to the number of generated signal events, as a function of the HVT resonance mass for the quark-antiquark production. The $A\times\epsilon$ is shown for each decay channel and the inclusive one. The decay of $W$ and $Z$ are to all flavors of leptons. The uncertainty shown represents the total statistical and systematic uncertainties.

Signal selection acceptance times efficiency (A$\times \epsilon$), defined as the ratio of the number of MC signal events in the category to the number of generated signal events, as a function of the HVT resonance mass for the quark-antiquark production. The $A\times\epsilon$ is shown for each decay channel and the inclusive one. The decay of $W$ and $Z$ are to all flavors of leptons. The uncertainty shown represents the total statistical and systematic uncertainties.

Observed and expected distributions of the $WZ$ invariant mass in the q$\bar{\mathrm q}$ category after applying all selection cuts. Background contributions are obtained from background-only likelihood fit to the data.

Observed and expected distributions of the $WZ$ invariant mass in the q$\bar{\mathrm q}$ category after applying all selection cuts. Background contributions are obtained from background-only likelihood fit to the data.

Observed and expected distributions of the $WZ$ invariant mass in the $VBF$ category after applying all selection cuts. Background contributions are obtained from background-only likelihood fit to the data.

Observed and expected distributions of the $WZ$ invariant mass in the $VBF$ category after applying all selection cuts. Background contributions are obtained from background-only likelihood fit to the data.

Observed and expected 95% C.L. upper limits on $\sigma\times$BR($W'\to W^\pm Z$) for the q$\bar{\mathrm q}$ production of a $W'$ boson in the HVT model as a function of its mass. The $\pm1\sigma$ and $\pm2\sigma$ uncertainty in the expected limits are given. Limits are calculated in the asymptotic approximation below 900 GeV and are obtained from pseudo-experiments above that.

Observed and expected 95% C.L. upper limits on $\sigma\times$BR($W'\to W^\pm Z$) for the q$\bar{\mathrm q}$ production of a $W'$ boson in the HVT model as a function of its mass. The $\pm1\sigma$ and $\pm2\sigma$ uncertainty in the expected limits are given. Limits are calculated in the asymptotic approximation below 900 GeV and are obtained from pseudo-experiments above that.

Observed and expected 95% C.L. upper limits on $\sigma\times$BR($W'\to W^\pm Z$) for the $VBF$ production of a $W'$ boson in the HVT model as a function of its mass. The $\pm1\sigma$ and $\pm2\sigma$ uncertainty are given in the expected limits. Limits are calculated in the asymptotic approximation below 700 GeV and are obtained from pseudo-experiments above that.

Observed and expected 95% C.L. upper limits on $\sigma\times$BR($W'\to W^\pm Z$) for the $VBF$ production of a $W'$ boson in the HVT model as a function of its mass. The $\pm1\sigma$ and $\pm2\sigma$ uncertainty are given in the expected limits. Limits are calculated in the asymptotic approximation below 700 GeV and are obtained from pseudo-experiments above that.

Observed and expected 95% C.L. upper limits on $\sigma\times$BR($H_5^\pm\to W^\pm Z$) of the Georgi-Machacek Model as a function of $m_{H_5^\pm}$. The $\pm1\sigma$ and $\pm2\sigma$ uncertainty in the expected limits are given. Limits are calculated in the asymptotic approximation below 700 GeV and are obtained from pseudo-experiments above that.

Observed and expected 95% C.L. upper limits on $\sigma\times$BR($H_5^\pm\to W^\pm Z$) of the Georgi-Machacek Model as a function of $m_{H_5^\pm}$. The $\pm1\sigma$ and $\pm2\sigma$ uncertainty in the expected limits are given. Limits are calculated in the asymptotic approximation below 700 GeV and are obtained from pseudo-experiments above that.

Observed and expected 95% C.L. upper limits on the parameter $\sin(\theta_H)$ of the Georgi-Machacek Model as a function of $m_{H_5^\pm}$. The $\pm1\sigma$ and $\pm2\sigma$ uncertainty are given in the expected limits. Limits are calculated in the asymptotic approximation below 700 GeV and are obtained from pseudo-experiments above that.

Observed and expected 95% C.L. upper limits on the parameter $\sin(\theta_H)$ of the Georgi-Machacek Model as a function of $m_{H_5^\pm}$. The $\pm1\sigma$ and $\pm2\sigma$ uncertainty are given in the expected limits. Limits are calculated in the asymptotic approximation below 700 GeV and are obtained from pseudo-experiments above that.

Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in SRC of the low-pT edge search. All statistical and systematic uncertainties of the expected background are included in the hatched band. An example signal from the $Z^{*}$ model with m(gluino) = 1000 GeV and m(neutralino1) = 900 GeV is overlaid.

Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in SRC-MET of the low-pT edge search. All statistical and systematic uncertainties of the expected background are included in the hatched band. An example signal from the $Z^{*}$ model with m(gluino) = 1000 GeV and m(neutralino1) = 900 GeV is overlaid.

Observed 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

Expected 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

Observed 95% CL exclusion contours from the low-p$_{T}$ signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

Expected 95% CL exclusion contours from the low-p$_{T}$ signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

Observed 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson and the lightest neutralino.

Expected 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson and the lightest neutralino.

Observed 95% CL exclusion contours from the low-p$_{T}$ signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson and the lightest neutralino.

Expected 95% CL exclusion contours from the low-p$_{T}$ signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson and the lightest neutralino.

Observed 95% CL exclusion contours from the on-Z signal regions on the gluino and next-to-lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.

Expected 95% CL exclusion contours from the on-Z signal regions on the gluino and next-to-lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.

Observed 95% CL exclusion contours from the on-Z signal regions on the squark and next-to-lightest neutralino masses in a SUSY scenario where squarks are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.

Expected 95% CL exclusion contours from the on-Z signal regions on the squark and next-to-lightest neutralino masses in a SUSY scenario where squarks are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.

Observed 95% CL exclusion contours from the on-Z signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson the lightest neutralino.

Expected 95% CL exclusion contours from the on-Z signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and the lightest neutralino.

Acceptance and efficiency in the on-Z bin for SR-medium for the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.

Acceptance and efficiency in the on-Z bin for SR-high for the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.

Acceptance and efficiency over the full $m_{ll}$ range for SR-low for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

Acceptance and efficiency over the full $m_{ll}$ range for SR-medium for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

Acceptance and efficiency over the full $m_{ll}$ range for SR-high for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

Acceptance and efficiency over the full $m_{ll}$ range for SRC for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

Acceptance and efficiency over the full $m_{ll}$ range for SRC-MET for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the on-Z $m_{ll}$ windows of SR-medium and SR-high, SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.

The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the on-Z $m_{ll}$ windows of SR-medium and SR-high, SUSY scenario where squarks are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.

The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the on-Z $m_{ll}$ windows of SR-medium and SR-high, in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson the lightest neutralino.

The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the signal regions, in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the low-p$_{T}$ signal regions, in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.

The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the signal regions, in a SUSYscenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson.

The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the low-p$_{T}$ signal regions, in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson.

Cutflow table for three benchmark signal points from the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino, with m(gluino) = 1395 GeV and m(neutralino2) = 505 GeV, m(gluino) = 920 GeV and m(neutralino2) = 230 GeV and m(gluino) = 940 GeV and m(neutralino2) = 660 GeV, in the on-$Z$ $m_{ll}$ bins of SR-medium and SR-high for the electron and muon channels separately. The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.

Cutflow table for a signal point from the SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino, with m(gluino) = 1000 GeV and m(neutralino1) = 800 GeV, m(gluino) = 1200 GeV and m(neutralino1) = 500 GeV and m(gluino) = 1400 GeV and m(neutralino1) = 100 GeV, in all m_{ll}$ bins of SR-low, SR-medium and SR-high for the electron and muon channels separately. The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.

Cutflow table for a signal point from the SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson, with m(gluino) = 600 GeV and m(neutralino1) = 560 GeV and m(gluino) = 1000 GeV and m(neutralino1) = 960 GeV, in all $m_{ll}$ bins of SRC and SRC-MET for the electron and muon channels separately. The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.

Signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.

Signal region used to derive the exclusion limit for the SUSY scenario where squarks are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.

Signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson the lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.

Signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson, corresponding to the SR determined to give the best expected limit for a given signal point.

Low-$p_{T}$ signal region used to derive the exclusion limit in the compressed region for the SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson, corresponding to the SR determined to give the best expected limit for a given signal point.

Signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.

Low-$p_{T}$ signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.

Differential cross sections in the full phase space obtained from the H->gammagamma and H->4l combined measurement for the transverse momentum of the leading jet pTj1. The first bin in the pTj1 distribution corresponds to the 0-jet bin in the Njets distribution. The NNLOPS ggF prediction scaled to the N3LO cross section is also provided.

Acceptance factors to extrapolate from the fiducial phase space to the total phase space, in bins of Higgs transverse momentum, in the 4l channel.

Acceptance factors to extrapolate from the fiducial phase space to the total phase space, in bins of Higgs transverse momentum, in the gamma gamma channel.

Acceptance factors to extrapolate from the fiducial phase space to the total phase space, in bins of Higgs rapidity, in the 4l channel.

Acceptance factors to extrapolate from the fiducial phase space to the total phase space, in bins of Higgs rapidity, in the gamma gamma channel.

Acceptance factors to extrapolate from the fiducial phase space to the total phase space, in bins of number of jets, in the 4l channel.

Acceptance factors to extrapolate from the fiducial phase space to the total phase space, in bins of number of jets, in the gamma gamma channel.

Acceptance factors to extrapolate from the fiducial phase space to the total phase space, in bins of the transverse momentum of the leading jet, in the 4l channel.

Acceptance factors to extrapolate from the fiducial phase space to the total phase space, in bins of the transverse momentum of the leading jet, in the gamma gamma channel.

Dijet mass spectra after the background only fit with the background prediction in the high-mass region with two b-tags.

Dijet mass spectra after the background only fit with the background prediction in the low-mass region with two b-tags.

The online b-tagging efficiency with respect to the offline b-tagging efficiency as a function of pT. The b-tagging online and offline working points correspond to an efficiency of 60% and 70%, respectively.

Observed and expected 95% credibility-level upper limits on the cross-section for the b* model in the high-mass region with inclusive b-jet selection.

Observed and expected 95% credibility-level upper limits on the cross-section times branching ratio for the SSM and leptophobic Z' models in the low- and high-mass region with two b-tags selection.

Observed and expected 95% credibility-level upper limits on the cross-section for DM Z' models in the low-mass region with two b-tags selection. The Z' is expected to decay to all five quark flavors other than the top quark and the mediator to SM quark coupling (gSM) equal to 0.1 is assumed.

Observed and expected 95% credibility-level upper limits on the cross-section times branching ratio for DM Z'->bb models in the high-mass region with two b-tags selection. The Z' is expected to decay to bb only and the mediator to SM quark coupling (gSM) equal to 0.25 is assumed.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances with intrinsic width smaller than the detector resolution. The width of the Gaussian reconstructed shape is dominated by the dijet mass resolution. The table shows the limits obtained from the high-mass inclusive one b-tag selection.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances with intrinsic width smaller than the detector resolution. The width of the Gaussian reconstructed shape is dominated by the dijet mass resolution. The table shows the limits obtained from the combined low- and high-mass two b-tags selection.

The mass distributions for the inclusive one b-tagged selection and two b-tagged selection using an integrated luminosity of 36.1 $fb^{-1}$. The inclusive one b-tagged Pythia8 MC distribution is normalized to the inclusive one b-tagged data. The two b-tagged Pythia8 MC distribution is normalized to the two b-tagged data. The systematic uncertainty band is dominated by the b-tagging scale factor and the b-jet energy scale.

Signal acceptance times efficiency for inclusive 1 b-tag and 2 b-tag categories as a function of the simulated b* and the Z' masses.

Signal acceptance times efficiency for 2 b-tag categories as a function of the simulated Z' masses.

The flavor composition of the simulated dijet background as a function of dijet mass before tagging. The fraction of the six combinations of the b-jet , c-jet and light-flavor jet are shown. All offline selections are applied.

The flavor composition of the simulated dijet background as a function of dijet mass with inclusive one b-tag. The fraction of the six combinations of the b-jet , c-jet and light-flavor jet are shown. All offline selections are applied.

The flavor composition of the simulated dijet background as a function of dijet mass with two b-tags. The fraction of the six combinations of the b-jet , c-jet and light-flavor jet are shown. All offline selections are applied.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the inclusive b-jet selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 3%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the inclusive b-jet selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 7%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the inclusive b-jet selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 10%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the inclusive b-jet selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 15%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the combined low- and high-mass two b-tags selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 3%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the combined low- and high-mass two b-tags selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 7%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the combined low- and high-mass two b-tags selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 10%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the combined low- and high-mass two b-tags selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 15%.

Non-prompt fraction of jpsi production in 5.02 TeV PbPb collision data as a function of pT for integrated centrality in the rapidity range |y| < 2.

The nuclear modification factor as a function of pT for the prompt jpsi for |y|<2, in 0--80% centrality bin.

The nuclear modification factor as a function of pT for the prompt jpsi for |y|<2, in 0--10%, 20--40%, and 40--80% centrality bin.

The nuclear modification factor as a function of pT for the non-prompt jpsi for |y|<2, in 0--80% centrality bin.

The nuclear modification factor as a function of pT for the non-prompt jpsi for |y|<2, in 0--10%, 20--40%, and 40--80% centrality bin.

The nuclear modification factor as a function of pT for the prompt and non-prompt jpsi for |y|<2, in 0--20% centrality bin.

The nuclear modification factor as a function of eta for the prompt jpsi for 9 < pT < 40 GeV, in 0--80% centrality bin.

The nuclear modification factor as a function of eta for the prompt jpsi for 9 < pT < 40 GeV, in 0--10%, 20--40%, and 40--80% centrality bin.

The nuclear modification factor as a function of eta for the non-prompt jpsi for 9 < pT < 40 GeV, in 0--80% centrality bin.

The nuclear modification factor as a function of eta for the non-prompt jpsi for 9 < pT < 40 GeV, in 0--10%, 20--40%, and 40--80% centrality bin.

The nuclear modification factor as a function of Npart for the prompt jpsi for |y|<2, and 9 < pT < 40 GeV

The nuclear modification factor as a function of Npart for the non-prompt jpsi for |y|<2, and 9 < pT < 40 GeV

The double ratio of nuclear modification factor as a function of Npart for the prompt jpsi and psi(2S) for |y|<2, and 9 < pT < 40 GeV

The double ratio nuclear modification factor as a function of Npart for the non-prompt jpsi and psi(2S) for |y|<2, and 9 < pT < 40 GeV

Acceptance for SR1 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR2 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR2 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR2 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR3 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR3 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR3 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR4 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR4 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR4 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR5 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR5 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for SR5 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for best expected CLS SR in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Acceptance for best expected CLS SR in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for best expected CLS SR in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR1 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR1 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR1 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR2 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR2 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR2 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR3 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR3 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR3 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR4 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR4 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR4 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR5 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR5 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for SR5 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for best expected CLS SR in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Detector efficiency for best expected CLS SR in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR1 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR1 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR1 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR1 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR1 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR1 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR2 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR2 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR2 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR2 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR2 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR2 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR3 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR3 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR3 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR3 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR3 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR3 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR4 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR4 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR4 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR4 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR4 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR4 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR5 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR5 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR5 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR5 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR5 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

SR5 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for the best expected SR in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR1 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR1 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR1 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR2 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR2 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR2 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR3 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR3 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR3 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR4 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR4 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR4 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR5 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR5 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for SR5 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for the best expected SR in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Upper limits on signal cross sections and exclusion limits at 95% CL for the best expected SR in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Minimum branching ratio excluded at 95% CL, assuming no sensitivity for other decay possibilities, in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Minimum branching ratio excluded at 95% CL, assuming no sensitivity for other decay possibilities, in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

Minimum branching ratio excluded at 95% CL, assuming no sensitivity for other decay possibilities, in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.

The signal region with the best expected CLS value for each signal in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

The signal region with the best expected CLS value for each signal in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

The signal region with the best expected CLS value for each signal in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.

Expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$\Delta m$ plane for the stop/scharm pair production scenario.

Expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$\Delta m$ plane for the stop/scharm pair production scenario.

Expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$\Delta m$ plane for the stop/scharm pair production scenario.

Observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$\Delta m$ plane for the stop/scharm pair production scenario.

Observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$\Delta m$ plane for the stop/scharm pair production scenario.

Observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$\Delta m$ plane for the stop/scharm pair production scenario.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR1. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR1. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR1. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR2. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR2. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR2. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR3. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR3. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR3. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR4. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR4. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR4. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR5. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR5. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR5. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (450,425)$ GeV signal point for signal region SR1.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (450,425)$ GeV signal point for signal region SR1.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (450,425)$ GeV signal point for signal region SR1.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (500,420)$ GeV signal point for signal region SR2.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (500,420)$ GeV signal point for signal region SR2.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (500,420)$ GeV signal point for signal region SR2.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (500,350)$ GeV signal point for signal region SR3.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (500,350)$ GeV signal point for signal region SR3.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (500,350)$ GeV signal point for signal region SR3.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (600,350)$ GeV signal point for signal region SR4.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (600,350)$ GeV signal point for signal region SR4.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (600,350)$ GeV signal point for signal region SR4.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (900,1)$ GeV signal point for signal region SR5.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (900,1)$ GeV signal point for signal region SR5.

Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (900,1)$ GeV signal point for signal region SR5.

Efficiencies for qqbar->X(J=1)->Wgamma signal events to pass the category selections as a function of the resonance mass.

Efficiencies for qqbar->X(J=1)->Hgamma signal events to pass the category selections as a function of the resonance mass.

Distribution of the reconstructed J+gamma invariant mass in Z+gamma search BTAG category.

Distribution of the reconstructed J+gamma invariant mass in Z+gamma search D2 category.

Distribution of the reconstructed J+gamma invariant mass in Z+gamma search VMASS category.

Distribution of the reconstructed J+gamma invariant mass in Z+gamma search ELSE category.

Distribution of the reconstructed J+gamma invariant mass in W+gamma search D2 category.

Distribution of the reconstructed J+gamma invariant mass in W+gamma search VMASS category.

Distribution of the reconstructed J+gamma invariant mass in W+gamma search ELSE category.

Distribution of the reconstructed J+gamma invariant mass in H+gamma search BTAG category.

The 95% CL upper limits on cross section times branching ratio for spin-0 resonance decaying to Zgamma.

The 95% CL upper limits on cross section times branching ratio for gluon-gluon fusion production spin-2 resonance decaying to Zgamma.

The 95% CL upper limits on cross section times branching ratio for quark-antiquark annihilation production spin-2 resonance decaying to Zgamma.

The 95% CL upper limits on cross section times branching ratio for spin-1 resonance decaying to Wgamma.

The 95% CL upper limits on cross section times branching ratio for spin-1 resonance decaying to Hgamma.

The observed and expected 95% CL upper limits on the production cross section times branching ratio for SM non-resonant Higgs pair production.

The $m_{\mathrm{eff}}$ distribution for events passing the signal region requirements except the $m_{\mathrm{eff}}$ requirement in SR2. Distributions for data, the estimated SM backgrounds, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $m_{\mathrm{eff}}$ selections in the signal region.

Expected 95% CL exclusion limits on wino $W/Z$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{12k} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Observed 95% CL exclusion limits on wino $W/Z$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{12k} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Expected 95% CL exclusion limits on wino $W/Z$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{i33} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Observed 95% CL exclusion limits on wino $W/Z$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{i33} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Expected 95% CL exclusion limits on wino $W/h$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{12k} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Observed 95% CL exclusion limits on wino $W/h$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{12k} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Expected 95% CL exclusion limits on wino $W/h$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{i33} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Observed 95% CL exclusion limits on wino $W/h$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{i33} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Expected 95% CL exclusion limits on $\tilde{\ell}/\tilde{\nu}$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{12k} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Observed 95% CL exclusion limits on $\tilde{\ell}/\tilde{\nu}$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{12k} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Expected 95% CL exclusion limits on $\tilde{\ell}/\tilde{\nu}$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{i33} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Observed 95% CL exclusion limits on $\tilde{\ell}/\tilde{\nu}$ NLSP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{i33} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Expected 95% CL exclusion limits on gluino NSLP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{12k} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Observed 95% CL exclusion limits on gluino NSLP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{12k} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Expected 95% CL exclusion limits on gluino NSLP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{i33} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Observed 95% CL exclusion limits on gluino NSLP pair production with RPV $\tilde{\chi}_1^0$ decays via $\lambda_{i33} \neq 0$ where $i,k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Expected 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Observed 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where the signal regions are not mutually exclusive, the observed $\mathrm{CL}_s$ value is taken from the signal region with the better expected $\mathrm{CL}_s$ value.

Observed exclusion limits on the $\tilde{\chi}_1^{\pm}/\tilde{\chi}_2^0$ masses in the context of the wino $W/Z$ RPV scenario with $\lambda_{12k} \neq 0$ couplings. The signal region used to obtain the limits is SR0A. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the $\tilde{\chi}_1^{\pm}/\tilde{\chi}_2^0$ masses in the context of the wino $W/Z$ RPV scenario with $\lambda_{i33} \neq 0$ couplings. The signal region used to obtain the limits is the combination of SR0A, SR1 and SR2. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the $\tilde{\chi}_1^{\pm}/\tilde{\chi}_2^0$ masses in the context of the wino $W/Z$ RPV scenario with $\lambda_{12k} \neq 0$ couplings. The signal region used to obtain the limits is SR0B. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the $\tilde{\chi}_1^{\pm}/\tilde{\chi}_2^0$ masses in the context of the wino $W/Z$ RPV scenario with $\lambda_{i33} \neq 0$ couplings. The signal region used to obtain the limits is the combination of SR0B, SR1 and SR2. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the $\tilde{\chi}_1^{\pm}/\tilde{\chi}_2^0$ masses in the context of the wino $W/h$ RPV scenario with $\lambda_{12k} \neq 0$ couplings. The signal region used to obtain the limits is SR0A. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the $\tilde{\chi}_1^{\pm}/\tilde{\chi}_2^0$ masses in the context of the wino $W/h$ RPV scenario with $\lambda_{i33} \neq 0$ couplings. The signal region used to obtain the limits is the combination of SR0A, SR1 and SR2. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the $\tilde{\chi}_1^{\pm}/\tilde{\chi}_2^0$ masses in the context of the wino $W/h$ RPV scenario with $\lambda_{12k} \neq 0$ couplings. The signal region used to obtain the limits is SR0B. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the $\tilde{\chi}_1^{\pm}/\tilde{\chi}_2^0$ masses in the context of the wino $W/h$ RPV scenario with $\lambda_{i33} \neq 0$ couplings. The signal region used to obtain the limits is the combination of SR0B, SR1 and SR2. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the slepton/sneutrino masses in the context of the slepton/sneutrino RPV scenario with $\lambda_{12k} \neq 0$ couplings. The signal region used to obtain the limits is SR0A. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the slepton/sneutrino masses in the context of the slepton/sneutrino RPV scenario with $\lambda_{i33} \neq 0$ couplings. The signal region used to obtain the limits is the combination of SR0A, SR1 and SR2. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the slepton/sneutrino masses in the context of the slepton/sneutrino RPV scenario with $\lambda_{12k} \neq 0$ couplings. The signal region used to obtain the limits is SR0B. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the slepton/sneutrino masses in the context of the slepton/sneutrino RPV scenario with $\lambda_{i33} \neq 0$ couplings. The signal region used to obtain the limits is the combination of SR0B, SR1 and SR2. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the gluino masses in the context of the gluino RPV scenario with $\lambda_{12k} \neq 0$ couplings. The signal region used to obtain the limits is SR0A. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the gluino masses in the context of the gluino RPV scenario with $\lambda_{i33} \neq 0$ couplings. The signal region used to obtain the limits is the combination of SR0A, SR1 and SR2. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the gluino masses in the context of the gluino RPV scenario with $\lambda_{12k} \neq 0$ couplings. The signal region used to obtain the limits is SR0B. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the gluino masses in the context of the gluino RPV scenario with $\lambda_{i33} \neq 0$ couplings. The signal region used to obtain the limits is the combination of SR0B, SR1 and SR2. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^{0}\tilde{\chi}_1^{0}$ masses in the context of the higgsino GGM scenario in SR0C. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

Observed exclusion limits on the $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^{0}\tilde{\chi}_1^{0}$ masses in the context of the higgsino GGM scenario in SR0D. All limits are computed at 95% CL. The grey numbers represent the 95% CL upper limits on the production cross-section (in fb) obtained using the signal efficiency and acceptance specific to this model.

The best expected exclusion power between signal regions at each signal point as is adopted in the limit calculation of the wino $W/Z$ model for $\lambda_{12k} \neq 0$ RPV couplings. For the $\lambda_{12k} \neq 0$ case, the results from SR0B are adopted everywhere in the final exclusion limit contours, as is found to be the most powerful signal region among SR0A and SR0B in the majority of the signal grid points of this model.

The best expected exclusion power between signal regions at each signal point as is adopted in the limit calculation of the wino $W/Z$ model for $\lambda_{i33} \neq 0$ RPV couplings. A combination of SR0A + SR1 + SR2 or SR0B + SR1 + SR2 is tested to detect the best expected limit; shown on the plot is the region (SR0A or SR0B) which is chosen to provide the best expected limit in combination with SR1 and SR2. The results from the combination SR0B + SR1 + SR2 are finally adopted everywhere in the final exclusion limit contour since they provide the best expected limit.

The best expected exclusion power between signal regions at each signal point as is adopted in the limit calculation of the wino $W/h$ model for $\lambda_{12k} \neq 0$ RPV couplings. For the $\lambda_{12k} \neq 0$ case, the results from SR0B are adopted everywhere in the final exclusion limit contours, as is found to be the most powerful signal region among SR0A and SR0B in the majority of the signal grid points of this model.

The best expected exclusion power between signal regions at each signal point as is adopted in the limit calculation of the wino $W/h$ model for $\lambda_{i33} \neq 0$ RPV couplings. A combination of SR0A + SR1 + SR2 or SR0B + SR1 + SR2 is tested to detect the best expected limit; shown on the plot is the region (SR0A or SR0B) which is chosen to provide the best expected limit in combination with SR1 and SR2. The results from the combination SR0B + SR1 + SR2 are finally adopted everywhere in the final exclusion limit contour since they provide the best expected limit.

The best expected exclusion power between signal regions at each signal point as is adopted in the limit calculation of the slepton/sneutrino model for $\lambda_{12k} \neq 0$ RPV couplings.

The best expected exclusion power between signal regions at each signal point as is adopted in the limit calculation of the slepton/sneutrino model for $\lambda_{i33} \neq 0$ RPV couplings. A combination of SR0A + SR1 + SR2 or SR0B + SR1 + SR2 is tested to detect the best expected limit; shown on the plot is the region (SR0A or SR0B) which is chosen to provide the best expected limit in combination with SR1 and SR2.

The best expected exclusion power between signal regions at each signal point as is adopted in the limit calculation of the gluino model for $\lambda_{12k} \neq 0$ RPV couplings.

The best expected exclusion power between signal regions at each signal point as is adopted in the limit calculation of the gluino model for $\lambda_{i33} \neq 0$ RPV couplings. A combination of SR0A + SR1 + SR2 or SR0B + SR1 + SR2 is tested to detect the best expected limit; shown on the plot is the region (SR0A or SR0B) which is chosen to provide the best expected limit in combination with SR1 and SR2.

The best expected exclusion power between the overlapping SR0C and SR0D at each signal point as is adopted in the limit combination of the GGM higgsino model.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{+}\tilde{\chi}_1^{-}$ $\lambda_{12k} \neq 0$ model fulfilling the selection criteria of SR0A. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^{0}$ $W/Z$ $\lambda_{12k} \neq 0$ model fulfilling the selection criteria of SR0A. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^{0}$ $W/h$ $\lambda_{12k} \neq 0$ model fulfilling the selection criteria of SR0A. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the slepton/sneutrino $\lambda_{12k} \neq 0$ model fulfilling the selection criteria of SR0A. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the gluino $\lambda_{12k} \neq 0$ model fulfilling the selection criteria of SR0A. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{+}\tilde{\chi}_1^{-}$ $\lambda_{12k} \neq 0$ model fulfilling the selection criteria of SR0B. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^{0}$ $W/Z$ $\lambda_{12k} \neq 0$ model fulfilling the selection criteria of SR0B. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^{0}$ $W/h$ $\lambda_{12k} \neq 0$ model fulfilling the selection criteria of SR0B. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the slepton/sneutrino $\lambda_{12k} \neq 0$ model fulfilling the selection criteria of SR0B. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the gluino $\lambda_{12k} \neq 0$ model fulfilling the selection criteria of SR0B. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the GGM Higgsino models with BR($\tilde{\chi}_1^0 \rightarrow Z \tilde{G}$)=100% and BR($\tilde{\chi}_1^0 \rightarrow Z \tilde{G}$)=50% fulfilling the selection criteria of SR0C. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the GGM Higgsino models with BR($\tilde{\chi}_1^0 \rightarrow Z \tilde{G}$)=100% and BR($\tilde{\chi}_1^0 \rightarrow Z \tilde{G}$)=50% fulfilling the selection criteria of SR0D. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{+}\tilde{\chi}_1^{-}$ $\lambda_{i33} \neq 0$ model fulfilling the selection criteria of SR1. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^{0}$ $W/Z$ $\lambda_{i33} \neq 0$ model fulfilling the selection criteria of SR1. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^{0}$ $W/h$ $\lambda_{i33} \neq 0$ model fulfilling the selection criteria of SR1. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the slepton/sneutrino $\lambda_{i33} \neq 0$ model fulfilling the selection criteria of SR1. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the gluino $\lambda_{i33} \neq 0$ model fulfilling the selection criteria of SR1. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{+}\tilde{\chi}_1^{-}$ $\lambda_{i33} \neq 0$ model fulfilling the selection criteria of SR2. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^{0}$ $W/Z$ $\lambda_{i33} \neq 0$ model fulfilling the selection criteria of SR2. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the Wino $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^{0}$ $W/h$ $\lambda_{i33} \neq 0$ model fulfilling the selection criteria of SR2. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the slepton/sneutrino $\lambda_{i33} \neq 0$ model fulfilling the selection criteria of SR2. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Acceptance ($A$) at particle level and selection efficiency ($\epsilon$) at reconstruction level for the gluino $\lambda_{i33} \neq 0$ model fulfilling the selection criteria of SR2. The implementation of "simple" cut selection at truth level uses the SimpleAnalysis framework and the code can be found in the Resources of the HepData entry for this paper.

Cutflow event yields in regions SR0A and SR0B for RPV models with the $\lambda_{12k} \neq 0$ coupling. All yields correspond to weighted events, so that effects from lepton reconstruction efficiencies, trigger corrections, pileup reweighting, etc., are included. They are normalized to the integrated luminosity of the data sample, $\int L dt = 36.1$ fb$^{-1}$. The "Initial" number indicates the weighted number of events before any selection cut is applied. The last entries show the normalized number of events surviving the selection requirements of SR0A and SR0B.

Cutflow event yields in regions SR0C and SR0D for GGM Higgsino models with BR($\tilde{\chi}_1^0 \rightarrow Z \tilde{G}$)=100% or BR($\tilde{\chi}_1^0 \rightarrow Z \tilde{G}$)=50%, and $\tilde{\chi}_1^{\pm}\tilde{\chi}_2^0\tilde{\chi}_1^0$ mass of 400 GeV. All yields correspond to weighted events, so that effects from lepton reconstruction efficiencies, trigger corrections, pileup reweighting, etc., are included. They are normalized to the integrated luminosity of the data sample, $\int L dt = 36.1$ fb$^{-1}$. The "Initial" number indicates the weighted number of events before any selection cut is applied. The "Generator Filter" step is applied during the MC generation of the simulated events; the BR=100% sample has a generator filter of $\geq 4e/\mu$ leptons with $p_{\mathrm{T}}>4$ GeV and $|\eta|<2.8$, and the BR=50% sample has a generator filter of $\geq 4 e/\mu/\tau_{\mathrm{had-vis}}$ leptons with $p_{\mathrm{T}}(e,\mu)>4$ GeV, $p_{\mathrm{T}}(\tau_{\mathrm{had-vis}}^{\mathrm{visible}})>15$ GeV and $|\eta|<2.8$. The $ZZ$ selection cutflow step refers to the mass window cut for the leading and subleading $Z$ boson candidate between $81.2-101.2$ GeV and $61.2-101.2$ GeV, respectively. The last entries show the efficiency of events surviving the selection requirements defined in SR0C and SR0D.

Cutflow event yields in region SR1 for RPV models with the $\lambda_{i33} \neq 0$ coupling. All yields correspond to weighted events, so that effects from lepton reconstruction efficiencies, trigger corrections, pileup reweighting, etc., are included. They are normalized to the integrated luminosity of the data sample, $\int L dt = 36.1$ fb$^{-1}$. The "Initial" number indicates the weighted number of events before any selection cut is applied. The last entries show the normalized number of events surviving the selection requirements of SR1.

Cutflow event yields in region SR2 for RPV models with the $\lambda_{i33} \neq 0$ coupling. All yields correspond to weighted events, so that effects from lepton reconstruction efficiencies, trigger corrections, pileup reweighting, etc., are included. They are normalized to the integrated luminosity of the data sample, $\int L dt = 36.1$ fb$^{-1}$. The "Initial" number indicates the weighted number of events before any selection cut is applied. The last entries show the normalized number of events surviving the selection requirements of SR2.

Cross sections for the slepton/snuetrino model for different NLSP masses.

Expected 95% CL limit on cross section times acceptance times branching ratio for each width and mass of Gaussian signal shape tested, in the region defined by |y*|<0.3.

Observed 95% CL limit on cross section times acceptance times branching ratio for each width and mass of Gaussian signal shape tested, in the region defined by |y*|<0.6.

Expected 95% CL limit on cross section times acceptance times branching ratio for each width and mass of Gaussian signal shape tested, in the region defined by |y*|<0.6.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-I, tanbeta 1, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-I only gluon-gluon fusion is used and the nb=2 category only.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-I, tanbeta 5, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-I only gluon-gluon fusion is used and the nb=2 category only.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-I, tanbeta 10, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-I only gluon-gluon fusion is used and the nb=2 category only.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-I, tanbeta 20, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-I only gluon-gluon fusion is used and the nb=2 category only.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-II, tanbeta 1, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-II both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-II, tanbeta 5, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-II both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-II, tanbeta 10, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-II both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-II, tanbeta 20, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-II both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the lepton specific, tanbeta 1, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For lepton specific only gluon-gluon fusion is used and the nb=2 category only.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the lepton specific, tanbeta 2, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For lepton specific only gluon-gluon fusion is used and the nb=2 category only.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the lepton specific, tanbeta 3, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For lepton specific only gluon-gluon fusion is used and the nb=2 category only.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the flipped, tanbeta 1, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For flipped both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the flipped, tanbeta 5, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For flipped both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the flipped, tanbeta 10, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For flipped both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.

The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the flipped, tanbeta 20, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For flipped both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 130 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 130 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 140 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 140 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 150 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 150 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 160 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 160 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 170 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 170 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 180 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 180 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 190 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 190 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 210 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 210 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 220 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 220 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 230 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 230 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 240 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 240 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 250 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 250 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 260 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 260 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 270 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 270 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 280 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 280 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 290 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 290 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 310 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 310 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 320 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 320 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 330 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 330 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 340 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 340 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 350 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 350 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 360 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 360 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 370 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 370 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 380 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 380 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 390 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 390 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 400 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 400 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 410 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 410 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 420 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 420 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 430 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 430 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 440 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 440 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 450 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 450 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 460 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 460 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 470 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 470 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 480 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 480 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 490 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 490 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 510 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 510 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 520 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 520 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 530 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 530 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 540 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 540 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 550 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 550 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 560 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 560 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 570 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 570 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 580 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 580 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 590 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 590 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 600 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 600 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 610 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 610 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 620 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 620 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 630 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 630 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 640 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 640 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 650 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 650 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 660 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 660 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 670 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 670 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 680 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 680 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 690 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 690 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 700 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 700 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 200 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 200 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 300 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 300 GeV for the nb >= 3 (3 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 500 GeV for the nb = 2 (2 tag) category.

The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 500 GeV for the nb >= 3 (3 tag) category.

Distributions of E_T^miss in the signal region of the had-had channel before the respective selection requirements, indicated by the vertical line and arrow, are applied. Here, &tau;₁ (&tau;₂) refers to the leading (subleading) &tau;_had. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty in the SM background. The error bars on the black data points represent the statistical uncertainty in the data yields. The dashed line shows the expected additional yields from a benchmark signal model. The rightmost bin includes the overflow.

<b>Exclusion contour (obs)</b> Expected (solid blue line) and observed (solid red line) exclusion-limit contours at 95% confidence level in the plane of top-squark and tau-slepton mass for the simplified model, obtained from the statistical combination of the lep-had and had-had channels, using full experimental and theory systematic uncertainties except the theoretical uncertainty in the signal cross section. The yellow band shows one-standard-deviation variations around the expected limit contour. The dotted red lines indicate how the observed limit moves when varying the signal cross section up or down by the corresponding uncertainty in the theoretical value. For comparison, the plot also shows the observed exclusion contour from the ATLAS Run-1 analysis as the area shaded in gray and the limit on the mass of the tau slepton (for a massless LSP) from the LEP experiments as a green band.

<b>Exclusion contour (exp)</b> Expected (solid blue line) and observed (solid red line) exclusion-limit contours at 95% confidence level in the plane of top-squark and tau-slepton mass for the simplified model, obtained from the statistical combination of the lep-had and had-had channels, using full experimental and theory systematic uncertainties except the theoretical uncertainty in the signal cross section. The yellow band shows one-standard-deviation variations around the expected limit contour. The dotted red lines indicate how the observed limit moves when varying the signal cross section up or down by the corresponding uncertainty in the theoretical value. For comparison, the plot also shows the observed exclusion contour from the ATLAS Run-1 analysis as the area shaded in gray and the limit on the mass of the tau slepton (for a massless LSP) from the LEP experiments as a green band.

Expected numbers of events from the SM background processes from the background fit and observed event yield in data for the signal regions in the lep-had and had-had channel, given for an integrated luminosity of 36.1 fb^-1. The expected yield for the signal model with m(t&#771;₁)=1100 GeV and m(&tau;&#771;₁)=590 GeV is shown for comparison. The uncertainties include both the statistical and systematic uncertainties and are truncated at zero. The total background from events with a fake tau lepton in the lep-had channel (fake &tau;_had + e /&mu;) is obtained from the fake-factor method.

Normalization factors obtained from the background-only fit. The normalization factor for tt&#772; events with fake tau leptons is only relevant for the had-had channel.

Left to right: observed 95% CL upper limits on the visible cross section (&lang; A &epsilon; &sigma; &rang;_obs⁹⁵) and on the number of signal events (S_obs⁹⁵ ). The third column (S_exp⁹⁵) shows the expected 95% CL upper limit on the number of signal events, given the expected number (and &plusmn; 1&sigma; excursions on the expectation) of background events. The last two columns indicate the CL_b value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)) and the corresponding significance (Z).

Signal acceptance A in percent for the signal region of the lep-had channel. The signal acceptance A is determined from a generator-level implementation of the analysis. It includes the branching ratios for the decays of the tau leptons. The selection efficiency &epsilon; is calculated using reconstructed objects, i.e. including all detector effects, and defined such that the event yields in the signal regions are given by the product A &middot; &epsilon; &middot; N_signal, where N_signal = &sigma; &middot; 36.1 fb^-1 and &sigma; is the theoretical prediction for the production cross section of top-squark pairs with the mass given on the horizontal axis.

Signal acceptance A in percent for the signal region of the had-had channel. The signal acceptance A is determined from a generator-level implementation of the analysis. It includes the branching ratios for the decays of the tau leptons. The selection efficiency &epsilon; is calculated using reconstructed objects, i.e. including all detector effects, and defined such that the event yields in the signal regions are given by the product A &middot; &epsilon; &middot; N_signal, where N_signal = &sigma; &middot; 36.1 fb^-1 and &sigma; is the theoretical prediction for the production cross section of top-squark pairs with the mass given on the horizontal axis.

Reconstruction efficiency &epsilon; in percent for the signal region of the lep-had channel. The signal acceptance A is determined from a generator-level implementation of the analysis. It includes the branching ratios for the decays of the tau leptons. The selection efficiency &epsilon; is calculated using reconstructed objects, i.e. including all detector effects, and defined such that the event yields in the signal regions are given by the product A &middot; &epsilon; &middot; N_signal, where N_signal = &sigma; &middot; 36.1 fb^-1 and &sigma; is the theoretical prediction for the production cross section of top-squark pairs with the mass given on the horizontal axis.

Reconstruction efficiency &epsilon; in percent for the signal region of the had-had channel. The signal acceptance A is determined from a generator-level implementation of the analysis. It includes the branching ratios for the decays of the tau leptons. The selection efficiency &epsilon; is calculated using reconstructed objects, i.e. including all detector effects, and defined such that the event yields in the signal regions are given by the product A &middot; &epsilon; &middot; N_signal, where N_signal = &sigma; &middot; 36.1 fb^-1 and &sigma; is the theoretical prediction for the production cross section of top-squark pairs with the mass given on the horizontal axis.

Upper exclusion limits at 95% confidence level on the observed cross section &sigma;_obs⁹⁵ for the simplified signal model as function of the top-squark mass m(t&#771;₁) and tau-slepton mass m(&tau;&#771;₁) in GeV.

Number of events passing each selection step of SR LH (lep-had channel) before (raw number) and after applying event-based weights (weighted) for signal point m(t&#771;₁) = 1100 GeV, m(&tau;&#771;₁) = 590 GeV. The preselection step here does not include the requirements on the tau p_T and the number of bjets.

Number of events passing each selection step of SR HH (had-had channel) before (raw number) and after applying event-based weights (weighted) for signal point m(t&#771;₁) = 1100 GeV, m(&tau;&#771;₁) = 590 GeV. The preselection step here does not include the requirements on the tau p_T and the number of bjets. Here, &tau;₁ (&tau;₂) refers to the leading (subleading) &tau;_had.

Distributions of ETmiss for data and the expected SM backgrounds in the 2l+jets channel for SR2-int/high, without the final ETmiss requirement applied. Two signal points are added for comparison.

Distributions of ETmiss for data and the expected SM backgrounds in the 2l+jets channel for SR2-low, without the final ETmiss requirement applied. Two signal points are added for comparison.

Distributions of ETmiss for data and the estimated SM backgrounds in the 3l channel for SR3-slep-a. Two signal points are added for comparison.

Distributions of ETmiss for data and the estimated SM backgrounds in the 3l channel for SR3-slep-b. Two signal points are added for comparison.

Distributions of the third leading lepton pT in SR3-slep-c,d,e. Two signal points are added for comparison.

Distributions of ETmiss for data and the estimated SM backgrounds in the 3l channel for SR3-WZ-0Ja,b,c. Two signal points are added for comparison.

Distributions of ETmiss for data and the estimated SM backgrounds in the 3l channel for SR3-WZ-1Ja. Two signal points are added for comparison.

Distributions of ETmiss for data and the estimated SM backgrounds in the 3l channel for SR3-WZ-1Jb. Two signal points are added for comparison.

Distributions of ETmiss for data and the estimated SM backgrounds in the 3l channel for SR3-WZ-1Jc. Two signal points are added for comparison.

Expected 95% CL exclusion limit for chargino-pair production.

Observed 95% CL exclusion limit for chargino-pair production.

Expected 95% CL exclusion limit for direct slepton production.

Observed 95% CL exclusion limit for direct slepton production.

Expected 95% CL exclusion limit for chargino-neutralino production with slepton-mediated decays.

Observed 95% CL exclusion limit for chargino-neutralino production with slepton-mediated decays.

Expected 95% CL exclusion limit for chargino-neutralino production with W/Z-mediated decays.

Observed 95% CL exclusion limit for chargino-neutralino production with W/Z-mediated decays.

The mT2 distributions for data and the estimated SM backgrounds in the exclusive SF signal regions of the 2l+0jets channel in the regions 111 < mll < 150 GeV (corresponding to SR2-SF-a,b,c,d). Two signal points are added for comparison.

The mT2 distributions for data and the estimated SM backgrounds in the exclusive SF signal regions of the 2l+0jets channel in the regions 150 < mll < 200 GeV (corresponding to SR2-SF-e,f,g,h). Two signal points are added for comparison.

The mT2 distributions for data and the estimated SM backgrounds in the exclusive SF signal regions of the 2l+0jets channel in the regions 200 < mll < 300 GeV (corresponding to SR2-SF-i,j,k,l). Two signal points are added for comparison.

The mT2 distributions for data and the estimated SM backgrounds in the exclusive SF signal regions of the 2l+0jets channel in the regions mll > 300 GeV (corresponding to SR2-SF-m). Two signal points are added for comparison.

Signal acceptance for C1C1 production in SR2-SFloose for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_1^\mp$ -> 2x $\ell \nu \widetilde{\chi}_1^0$ .

Signal efficiency for C1C1 production in SR2-SFloose for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_1^\mp$ -> 2x $\ell \nu \widetilde{\chi}_1^0$.

Signal acceptance for C1C1 production in SR2-SFtight for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_1^\mp$ -> 2x $\ell \nu \widetilde{\chi}_1^0$.

Signal efficiency for C1C1 production in SR2-SFtight for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_1^\mp$ -> 2x $\ell \nu \widetilde{\chi}_1^0$.

Signal acceptance for C1C1 production in SR2-DF100 for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_1^\mp$ -> 2x $\ell \nu \widetilde{\chi}_1^0$.

Signal efficiency for C1C1 production in SR2-DF100 for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_1^\mp$ -> 2x $\ell \nu \widetilde{\chi}_1^0$.

Signal acceptance for C1C1 production in SR2-DF150 for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_1^\mp$ -> 2x $\ell \nu \widetilde{\chi}_1^0$.

Signal efficiency for C1C1 production in SR2-DF150 for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_1^\mp$ -> 2x $\ell \nu \widetilde{\chi}_1^0$.

Signal acceptance for C1C1 production in SR2-DF200 for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_1^\mp$ -> 2x $\ell \nu \widetilde{\chi}_1^0$.

Signal efficiency for C1C1 production in SR2-DF200 for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_1^\mp$ -> 2x $\ell \nu \widetilde{\chi}_1^0$.

Signal acceptance for C1C1 production in SR2-DF300 for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_1^\mp$ -> 2x $\ell \nu \widetilde{\chi}_1^0$.

Signal efficiency for C1C1 production in SR2-DF300 for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_1^\mp$ -> 2x $\ell \nu \widetilde{\chi}_1^0$.

Signal acceptance for direct Slepton production in SR2-SF-Loose for the process P P -> $\tilde{\ell}^\pm \tilde{\ell}^\mp$ -> $\ell^\pm \ell^\mp \widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal efficiency for direct Slepton production in SR2-SF-Loose for the process P P -> $\tilde{\ell}^\pm \tilde{\ell}^\mp$ -> $\ell^\pm \ell^\mp \widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal acceptance for direct Slepton production in SR2-SF-Tight for the process P P -> $\tilde{\ell}^\pm \tilde{\ell}^\mp$ -> $\ell^\pm \ell^\mp \widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal efficiency for direct Slepton production in SR2-SF-Tight for the process P P -> $\tilde{\ell}^\pm \tilde{\ell}^\mp$ -> $\ell^\pm \ell^\mp \widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal acceptance for C1N2 production in SR2-low for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $W$(->2j) $Z$(->2l) $\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal efficiency for C1N2 production in SR2-low for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $W$(->2j) $Z$(->2l) $\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal acceptance for C1N2 production in SR2-int for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $W$(->2j) $Z$(->2l) $\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal efficiency for C1N2 production in SR2-int for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $W$(->2j) $Z$(->2l) $\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal acceptance for C1N2 production in SR2-high for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $W$(->2j) $Z$(->2l) $\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal efficiency for C1N2 production in SR2-high for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $W$(->2j) $Z$(->2l) $\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal acceptance for Slep production in SR3-slepa for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $\tilde{\ell}_L \tilde{\ell}_L l (\tilde{\nu}\nu), l \tilde{\nu} \tilde{\ell}_L (\tilde{\nu}\nu)$ -> $l \nu \widetilde{\chi}_1^0 l l (\nu \nu) \widetilde{\chi}_1^0$.

Signal efficiency for Slep production in SR3-slepa for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $\tilde{\ell}_L \tilde{\ell}_L l (\tilde{\nu}\nu), l \tilde{\nu} \tilde{\ell}_L (\tilde{\nu}\nu)$ -> $l \nu \widetilde{\chi}_1^0 l l (\nu \nu) \widetilde{\chi}_1^0$.

Signal acceptance for Slep production in SR3-slepb for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $\tilde{\ell}_L \tilde{\ell}_L l (\tilde{\nu}\nu), l \tilde{\nu} \tilde{\ell}_L (\tilde{\nu}\nu)$ -> $l \nu \widetilde{\chi}_1^0 l l (\nu \nu) \widetilde{\chi}_1^0$.

Signal efficiency for Slep production in SR3-slepb for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $\tilde{\ell}_L \tilde{\ell}_L l (\tilde{\nu}\nu), l \tilde{\nu} \tilde{\ell}_L (\tilde{\nu}\nu)$ -> $l \nu \widetilde{\chi}_1^0 l l (\nu \nu) \widetilde{\chi}_1^0$.

Signal acceptance for Slep production in SR3-slepc for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $\tilde{\ell}_L \tilde{\ell}_L l (\tilde{\nu}\nu), l \tilde{\nu} \tilde{\ell}_L (\tilde{\nu}\nu)$ -> $l \nu \widetilde{\chi}_1^0 l l (\nu \nu) \widetilde{\chi}_1^0$.

Signal efficiency for Slep production in SR3-slepc for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $\tilde{\ell}_L \tilde{\ell}_L l (\tilde{\nu}\nu), l \tilde{\nu} \tilde{\ell}_L (\tilde{\nu}\nu)$ -> $l \nu \widetilde{\chi}_1^0 l l (\nu \nu) \widetilde{\chi}_1^0$.

Signal acceptance for Slep production in SR3-slepd for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $\tilde{\ell}_L \tilde{\ell}_L l (\tilde{\nu}\nu), l \tilde{\nu} \tilde{\ell}_L (\tilde{\nu}\nu)$ -> $l \nu \widetilde{\chi}_1^0 l l (\nu \nu) \widetilde{\chi}_1^0$.

Signal efficiency for Slep production in SR3-slepd for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $\tilde{\ell}_L \tilde{\ell}_L l (\tilde{\nu}\nu), l \tilde{\nu} \tilde{\ell}_L (\tilde{\nu}\nu)$ -> $l \nu \widetilde{\chi}_1^0 l l (\nu \nu) \widetilde{\chi}_1^0$.

Signal acceptance for Slep production in SR3-slepe for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $\tilde{\ell}_L \tilde{\ell}_L l (\tilde{\nu}\nu), l \tilde{\nu} \tilde{\ell}_L (\tilde{\nu}\nu)$ -> $l \nu \widetilde{\chi}_1^0 l l (\nu \nu) \widetilde{\chi}_1^0$.

Signal efficiency for Slep production in SR3-slepe for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $\tilde{\ell}_L \tilde{\ell}_L l (\tilde{\nu}\nu), l \tilde{\nu} \tilde{\ell}_L (\tilde{\nu}\nu)$ -> $l \nu \widetilde{\chi}_1^0 l l (\nu \nu) \widetilde{\chi}_1^0$.

Signal acceptance for WZ production in SR3-WZ-0Ja for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $W$(->l $\nu$) $Z$(->2l) $\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal efficiency for WZ production in SR3-WZ-0Ja for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $W$(->l $\nu$) $Z$(->2l) $\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal acceptance for WZ production in SR3-WZ-0Jb for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $W$(->l $\nu$) $Z$(->2l) $\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal efficiency for WZ production in SR3-WZ-0Jb for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $W$(->l $\nu$) $Z$(->2l) $\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal acceptance for WZ production in SR3-WZ-0Jc for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $W$(->l $\nu$) $Z$(->2l) $\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal efficiency for WZ production in SR3-WZ-0Jc for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $W$(->l $\nu$) $Z$(->2l) $\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal acceptance for WZ production in SR3-WZ-1Ja for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $W$(->l $\nu$) $Z$(->2l) $\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal efficiency for WZ production in SR3-WZ-1Ja for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $W$(->l $\nu$) $Z$(->2l) $\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal acceptance for WZ production in SR3-WZ-1Jb for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $W$(->l $\nu$) $Z$(->2l) $\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal efficiency for WZ production in SR3-WZ-1Jb for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $W$(->l $\nu$) $Z$(->2l) $\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal acceptance for WZ production in SR3-WZ-1Jc for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $W$(->l $\nu$) $Z$(->2l) $\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal efficiency for WZ production in SR3-WZ-1Jc for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $W$(->l $\nu$) $Z$(->2l) $\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

Signal regions contributing to the observed exclusion limit for chargino-neutralino production with W/Z-mediated decays.

Expected 95% CL exclusion limit for chargino-neutralino production with W/Z-mediated decays in the 2l+jets channel.

Observed 95% CL exclusion limit for chargino-neutralino production with W/Z-mediated decays in the 2l+jets channel.

Expected 95% CL exclusion limit for chargino-neutralino production with W/Z-mediated decays in the 3l channel.

Observed 95% CL exclusion limit for chargino-neutralino production with W/Z-mediated decays in the 2l+jets channel.

Expected 95% CL exclusion limit for left-handed slepton production.

Observed 95% CL exclusion limit for left-handed slepton production.

Expected 95% CL exclusion limit for right-handed slepton production.

Observed 95% CL exclusion limit for right-handed slepton production.

95% upper limit on production cross-section for chargino-pair production.

95% upper limit on production cross-section for direct slepton production.

95% upper limit on production cross-section for chargino-neutralino production with slepton-mediated decays.

95% upper limit on production cross-section for chargino-neutralino production with W/Z-mediated decays

<b>Cutflow 1</b> Event counts for a signal point in SR2-SF-loose for the process P P -> $\tilde{\ell}^\pm \tilde{\ell}^\mp$ -> $\ell^\pm \ell^\mp \widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

<b>Cutflow 2</b> Event counts for a signal point in SR2-SF-loose and SR2-DF-100 for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $\tilde{\ell}_L \tilde{\ell}_L l (\tilde{\nu}\nu), l \tilde{\nu} \tilde{\ell}_L (\tilde{\nu}\nu)$ -> $l \nu \widetilde{\chi}_1^0 l l (\nu \nu) \widetilde{\chi}_1^0$.

<b>Cutflow 3</b> Event counts for two signal points in SR2-int for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $\tilde{\ell}_L \tilde{\ell}_L l (\tilde{\nu}\nu), l \tilde{\nu} \tilde{\ell}_L (\tilde{\nu}\nu)$ -> $l \nu \widetilde{\chi}_1^0 l l (\nu \nu) \widetilde{\chi}_1^0$.

<b>Cutflow 4</b> Event counts for two signal points in SR2-low for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_1^\mp$ -> 2x $\ell \nu \widetilde{\chi}_1^0$.

<b>Cutflow 5</b> Event counts for two signal points in SR3-WZ-0Ja/b/c and SR3-WZ-1Ja/b/c for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $W$(->l $\nu$) $Z$(->2l) $\widetilde{\chi}_1^0 \widetilde{\chi}_1^0$.

<b>Cutflow 6</b> Event counts for two signal points in SR3-slepa-e for the process P P -> $\widetilde{\chi}_1^\pm \widetilde{\chi}_2^0$ -> $\tilde{\ell}_L \tilde{\ell}_L l (\tilde{\nu}\nu), l \tilde{\nu} \tilde{\ell}_L (\tilde{\nu}\nu)$ -> $l \nu \widetilde{\chi}_1^0 l l (\nu \nu) \widetilde{\chi}_1^0$.

Statistical correlation matrix between |$p_{out}^{t\bar{t}}$| in the 4-jet exclusive configuration and |$p_{out}^{t\bar{t}}$| in the 6-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between |$p_{out}^{t\bar{t}}$| in the 4-jet exclusive configuration and $p_{T}^{t,had}$ in the 6-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between |$p_{out}^{t\bar{t}}$| in the 4-jet exclusive configuration and $p_{T}^{t\bar{t}}$ in the 6-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between |$p_{out}^{t\bar{t}}$| in the 4-jet exclusive configuration and |$p_{out}^{t\bar{t}}$| in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between |$p_{out}^{t\bar{t}}$| in the 4-jet exclusive configuration and $p_{T}^{t,had}$ in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between |$p_{out}^{t\bar{t}}$| in the 4-jet exclusive configuration and $p_{T}^{t\bar{t}}$ in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between |$p_{out}^{t\bar{t}}$| in the 4-jet exclusive configuration and |$p_{out}^{t\bar{t}}$| in the 4-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t,had}$ in the 4-jet exclusive configuration and $p_{T}^{t,had}$ in the 4-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t,had}$ in the 4-jet exclusive configuration and $p_{T}^{t\bar{t}}$ in the 4-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t,had}$ in the 4-jet exclusive configuration and |$p_{out}^{t\bar{t}}$| in the 6-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t,had}$ in the 4-jet exclusive configuration and $p_{T}^{t,had}$ in the 6-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t,had}$ in the 4-jet exclusive configuration and $p_{T}^{t\bar{t}}$ in the 6-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t,had}$ in the 4-jet exclusive configuration and |$p_{out}^{t\bar{t}}$| in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t,had}$ in the 4-jet exclusive configuration and $p_{T}^{t,had}$ in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t,had}$ in the 4-jet exclusive configuration and $p_{T}^{t\bar{t}}$ in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t,had}$ in the 4-jet exclusive configuration and |$p_{out}^{t\bar{t}}$| in the 4-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t\bar{t}}$ in the 4-jet exclusive configuration and $p_{T}^{t\bar{t}}$ in the 4-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t\bar{t}}$ in the 4-jet exclusive configuration and |$p_{out}^{t\bar{t}}$| in the 6-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t\bar{t}}$ in the 4-jet exclusive configuration and $p_{T}^{t,had}$ in the 6-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t\bar{t}}$ in the 4-jet exclusive configuration and $p_{T}^{t\bar{t}}$ in the 6-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t\bar{t}}$ in the 4-jet exclusive configuration and |$p_{out}^{t\bar{t}}$| in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t\bar{t}}$ in the 4-jet exclusive configuration and $p_{T}^{t,had}$ in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t\bar{t}}$ in the 4-jet exclusive configuration and $p_{T}^{t\bar{t}}$ in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t\bar{t}}$ in the 4-jet exclusive configuration and |$p_{out}^{t\bar{t}}$| in the 4-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between |$p_{out}^{t\bar{t}}$| in the 6-jet inclusive configuration and |$p_{out}^{t\bar{t}}$| in the 6-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between |$p_{out}^{t\bar{t}}$| in the 6-jet inclusive configuration and $p_{T}^{t,had}$ in the 6-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between |$p_{out}^{t\bar{t}}$| in the 6-jet inclusive configuration and $p_{T}^{t\bar{t}}$ in the 6-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between |$p_{out}^{t\bar{t}}$| in the 6-jet inclusive configuration and |$p_{out}^{t\bar{t}}$| in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between |$p_{out}^{t\bar{t}}$| in the 6-jet inclusive configuration and $p_{T}^{t,had}$ in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between |$p_{out}^{t\bar{t}}$| in the 6-jet inclusive configuration and $p_{T}^{t\bar{t}}$ in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between |$p_{out}^{t\bar{t}}$| in the 6-jet inclusive configuration and |$p_{out}^{t\bar{t}}$| in the 4-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t,had}$ in the 6-jet inclusive configuration and $p_{T}^{t,had}$ in the 6-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t,had}$ in the 6-jet inclusive configuration and $p_{T}^{t\bar{t}}$ in the 6-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t,had}$ in the 6-jet inclusive configuration and |$p_{out}^{t\bar{t}}$| in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t,had}$ in the 6-jet inclusive configuration and $p_{T}^{t,had}$ in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t,had}$ in the 6-jet inclusive configuration and $p_{T}^{t\bar{t}}$ in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t,had}$ in the 6-jet inclusive configuration and |$p_{out}^{t\bar{t}}$| in the 4-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t\bar{t}}$ in the 6-jet inclusive configuration and $p_{T}^{t\bar{t}}$ in the 6-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t\bar{t}}$ in the 6-jet inclusive configuration and |$p_{out}^{t\bar{t}}$| in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t\bar{t}}$ in the 6-jet inclusive configuration and $p_{T}^{t,had}$ in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t\bar{t}}$ in the 6-jet inclusive configuration and $p_{T}^{t\bar{t}}$ in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t\bar{t}}$ in the 6-jet inclusive configuration and |$p_{out}^{t\bar{t}}$| in the 4-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between |$p_{out}^{t\bar{t}}$| in the 5-jet exclusive configuration and |$p_{out}^{t\bar{t}}$| in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between |$p_{out}^{t\bar{t}}$| in the 5-jet exclusive configuration and $p_{T}^{t,had}$ in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between |$p_{out}^{t\bar{t}}$| in the 5-jet exclusive configuration and $p_{T}^{t\bar{t}}$ in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between |$p_{out}^{t\bar{t}}$| in the 5-jet exclusive configuration and |$p_{out}^{t\bar{t}}$| in the 4-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t,had}$ in the 5-jet exclusive configuration and $p_{T}^{t,had}$ in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t,had}$ in the 5-jet exclusive configuration and $p_{T}^{t\bar{t}}$ in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t,had}$ in the 5-jet exclusive configuration and |$p_{out}^{t\bar{t}}$| in the 4-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t\bar{t}}$ in the 5-jet exclusive configuration and $p_{T}^{t\bar{t}}$ in the 5-jet exclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between $p_{T}^{t\bar{t}}$ in the 5-jet exclusive configuration and |$p_{out}^{t\bar{t}}$| in the 4-jet inclusive configuration, obtained through the Bootstrap Method.

Statistical correlation matrix between |$p_{out}^{t\bar{t}}$| in the 4-jet inclusive configuration and |$p_{out}^{t\bar{t}}$| in the 4-jet inclusive configuration, obtained through the Bootstrap Method.

Covariance matrix of the absolute cross-section as function of |$p_{out}^{t\bar{t}}$| in the 4-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Covariance matrix of the relative cross-section as function of |$p_{out}^{t\bar{t}}$| in the 4-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Covariance matrix of the absolute cross-section as function of $p_{T}^{t,had}$ in the 4-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Covariance matrix of the relative cross-section as function of $p_{T}^{t,had}$ in the 4-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Covariance matrix of the absolute cross-section as function of $p_{T}^{t\bar{t}}$ in the 4-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Covariance matrix of the relative cross-section as function of $p_{T}^{t\bar{t}}$ in the 4-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Covariance matrix of the absolute cross-section as function of |$p_{out}^{t\bar{t}}$| in the 6-jet inclusive configuration, accounting for the statistical and systematic uncertainties.

Covariance matrix of the relative cross-section as function of |$p_{out}^{t\bar{t}}$| in the 6-jet inclusive configuration, accounting for the statistical and systematic uncertainties.

Covariance matrix of the absolute cross-section as function of $p_{T}^{t,had}$ in the 6-jet inclusive configuration, accounting for the statistical and systematic uncertainties.

Covariance matrix of the relative cross-section as function of $p_{T}^{t,had}$ in the 6-jet inclusive configuration, accounting for the statistical and systematic uncertainties.

Covariance matrix of the absolute cross-section as function of $p_{T}^{t\bar{t}}$ in the 6-jet inclusive configuration, accounting for the statistical and systematic uncertainties.

Covariance matrix of the relative cross-section as function of $p_{T}^{t\bar{t}}$ in the 6-jet inclusive configuration, accounting for the statistical and systematic uncertainties.

Covariance matrix of the absolute cross-section as function of |$p_{out}^{t\bar{t}}$| in the 5-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Covariance matrix of the relative cross-section as function of |$p_{out}^{t\bar{t}}$| in the 5-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Covariance matrix of the absolute cross-section as function of $p_{T}^{t,had}$ in the 5-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Covariance matrix of the relative cross-section as function of $p_{T}^{t,had}$ in the 5-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Covariance matrix of the absolute cross-section as function of $p_{T}^{t\bar{t}}$ in the 5-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Covariance matrix of the relative cross-section as function of $p_{T}^{t\bar{t}}$ in the 5-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Covariance matrix of the absolute cross-section as function of |$p_{out}^{t\bar{t}}$| in the 4-jet inclusive configuration, accounting for the statistical and systematic uncertainties.

Covariance matrix of the relative cross-section as function of |$p_{out}^{t\bar{t}}$| in the 4-jet inclusive configuration, accounting for the statistical and systematic uncertainties.

Correlation matrix of the absolute cross-section as function of |$p_{out}^{t\bar{t}}$| in the 4-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Correlation matrix of the relative cross-section as function of |$p_{out}^{t\bar{t}}$| in the 4-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Correlation matrix of the absolute cross-section as function of $p_{T}^{t,had}$ in the 4-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Correlation matrix of the relative cross-section as function of $p_{T}^{t,had}$ in the 4-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Correlation matrix of the absolute cross-section as function of $p_{T}^{t\bar{t}}$ in the 4-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Correlation matrix of the relative cross-section as function of $p_{T}^{t\bar{t}}$ in the 4-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Correlation matrix of the absolute cross-section as function of |$p_{out}^{t\bar{t}}$| in the 6-jet inclusive configuration, accounting for the statistical and systematic uncertainties.

Correlation matrix of the relative cross-section as function of |$p_{out}^{t\bar{t}}$| in the 6-jet inclusive configuration, accounting for the statistical and systematic uncertainties.

Correlation matrix of the absolute cross-section as function of $p_{T}^{t,had}$ in the 6-jet inclusive configuration, accounting for the statistical and systematic uncertainties.

Correlation matrix of the relative cross-section as function of $p_{T}^{t,had}$ in the 6-jet inclusive configuration, accounting for the statistical and systematic uncertainties.

Correlation matrix of the absolute cross-section as function of $p_{T}^{t\bar{t}}$ in the 6-jet inclusive configuration, accounting for the statistical and systematic uncertainties.

Correlation matrix of the relative cross-section as function of $p_{T}^{t\bar{t}}$ in the 6-jet inclusive configuration, accounting for the statistical and systematic uncertainties.

Correlation matrix of the absolute cross-section as function of |$p_{out}^{t\bar{t}}$| in the 5-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Correlation matrix of the relative cross-section as function of |$p_{out}^{t\bar{t}}$| in the 5-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Correlation matrix of the absolute cross-section as function of $p_{T}^{t,had}$ in the 5-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Correlation matrix of the relative cross-section as function of $p_{T}^{t,had}$ in the 5-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Correlation matrix of the absolute cross-section as function of $p_{T}^{t\bar{t}}$ in the 5-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Correlation matrix of the relative cross-section as function of $p_{T}^{t\bar{t}}$ in the 5-jet exclusive configuration, accounting for the statistical and systematic uncertainties.

Correlation matrix of the absolute cross-section as function of |$p_{out}^{t\bar{t}}$| in the 4-jet inclusive configuration, accounting for the statistical and systematic uncertainties.

Correlation matrix of the relative cross-section as function of |$p_{out}^{t\bar{t}}$| in the 4-jet inclusive configuration, accounting for the statistical and systematic uncertainties.

Systematic uncertanties for the absolute differential cross-section at particle-level for |$p_{out}^{t\bar{t}}$| in the 4-jet exclusive configuration. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Systematic uncertanties for the relative differential cross-section at particle-level for |$p_{out}^{t\bar{t}}$| in the 4-jet exclusive configuration. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Systematic uncertanties for the absolute differential cross-section at particle-level for $p_{T}^{t,had}$ in the 4-jet exclusive configuration. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Systematic uncertanties for the relative differential cross-section at particle-level for $p_{T}^{t,had}$ in the 4-jet exclusive configuration. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Systematic uncertanties for the absolute differential cross-section at particle-level for $p_{T}^{t\bar{t}}$ in the 4-jet exclusive configuration. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Systematic uncertanties for the relative differential cross-section at particle-level for $p_{T}^{t\bar{t}}$ in the 4-jet exclusive configuration. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Systematic uncertanties for the absolute differential cross-section at particle-level for |$p_{out}^{t\bar{t}}$| in the 6-jet inclusive configuration. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Systematic uncertanties for the relative differential cross-section at particle-level for |$p_{out}^{t\bar{t}}$| in the 6-jet inclusive configuration. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Systematic uncertanties for the absolute differential cross-section at particle-level for $p_{T}^{t,had}$ in the 6-jet inclusive configuration. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Systematic uncertanties for the relative differential cross-section at particle-level for $p_{T}^{t,had}$ in the 6-jet inclusive configuration. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Systematic uncertanties for the absolute differential cross-section at particle-level for $p_{T}^{t\bar{t}}$ in the 6-jet inclusive configuration. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Systematic uncertanties for the relative differential cross-section at particle-level for $p_{T}^{t\bar{t}}$ in the 6-jet inclusive configuration. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Systematic uncertanties for the absolute differential cross-section at particle-level for |$p_{out}^{t\bar{t}}$| in the 5-jet exclusive configuration. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Systematic uncertanties for the relative differential cross-section at particle-level for |$p_{out}^{t\bar{t}}$| in the 5-jet exclusive configuration. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Systematic uncertanties for the absolute differential cross-section at particle-level for $p_{T}^{t,had}$ in the 5-jet exclusive configuration. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Systematic uncertanties for the relative differential cross-section at particle-level for $p_{T}^{t,had}$ in the 5-jet exclusive configuration. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Systematic uncertanties for the absolute differential cross-section at particle-level for $p_{T}^{t\bar{t}}$ in the 5-jet exclusive configuration. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Systematic uncertanties for the relative differential cross-section at particle-level for $p_{T}^{t\bar{t}}$ in the 5-jet exclusive configuration. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Systematic uncertanties for the absolute differential cross-section at particle-level for |$p_{out}^{t\bar{t}}$| in the 4-jet inclusive configuration. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Systematic uncertanties for the relative differential cross-section at particle-level for |$p_{out}^{t\bar{t}}$| in the 4-jet inclusive configuration. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Measured differential cross section with associated uncertainties as a function of COS(THETA*). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of DELTAYRAP(2GAMMA). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of MULT(JET,PT>30 GEV). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of MULT(JET,PT>50 GEV). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of PT(JET1). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of PT(JET2). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of HT. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of YRAP(JET1). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of YRAP(JET2). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of M(2JET). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of DELTAYRAP(2JET). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of ABSDPHI(2JET). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of DPHI(2JET). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of PT(2GAMMA2JET). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of DPHI(2GAMMA,2JET). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of TAUJET. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of SUM(TAUJET). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of PT(2GAMMA) [NJET=0,PT>30 GEV]. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of PT(2GAMMA) [NJET=1,PT>30 GEV]. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of PT(2GAMMA) [NJET=2,PT>30 GEV]. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of PT(2GAMMA) [NJET>=3,PT>30 GEV]. Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

The measured cross sections or cross section limits of the diphoton, VBF-enhanced, Nlepton $\geq$ 1, high $E_{T}^{miss}$, and ttH-enhanced fiducial regions are shown.

Measured differential cross section with associated uncertainties as a function of diphoton transverse momentum in bins of ABS(COS(THETA*)). Each systematic uncertainty sources is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.Each systematic uncertainty sources is fully uncorrelated with the other sources.

Non-perturbative correction factors in percent accounting for the impact of hadronisation and the underlying event activity for all measured variables and fiducial regions. Regions of phase space where no reliable estimate could be obtained are listed as 100 without uncertainties. Uncertainties are evaluated by deriving these factors using different generators and tunes as described in the text. No factor are given for the Nlepton $\geq$ 1 and High-$E_{T}^{miss}$ fiducial regions as the gluon fusion contamination in both is negligible.

Isolation efficiencies in percent for gluon fusion $H\rightarrow\gamma\gamma$ for each fiducial region/variable bin measured in this analysis. The isolation efficiency is defined as the probability for both photons to fulfil the isolation criteria (as described in Section 9.1) for events that pass the diphoton kinematic criteria. Regions of phase space where no reliable estimate could be obtained are listed as 100 without uncertainties. Uncertainties are assigned in the same way as for the non-perturbative correction factors: by varying the fragmentation and underlying event modelling. These factors can be multiplied by the kinematic acceptance factors (see Table 29) to extrapolate an inclusive gluon fusion Higgs prediction to the fiducial volume used in this analysis. No factors for the Nlepton $\geq$ 1 and High $E_{T}^{miss}$ fiducial regions are provided as the gluon fusion contamination is negligible.

Combined non-perturbative (Table 27) and particle-level isolation correction factors (Table 28) in percent accounting for the impact of hadronisation and the underlying event activity for all measured variables and fiducial regions. Regions of phase space where no reliable estimate could be obtained are listed as 100 without uncertainties. The uncertainties on the combined values properly take into account the correlations between both multiplicative factors.

Diphoton kinematic acceptances in percent for gluon-gluon fusion for the diphoton fiducial region and all differential variable bins studied in this paper, defined as the probability to fulfill the diphoton kinematic criteria: $p_{T}$/$m_{\gamma\gamma}$ < 0.35 (0.25) for the leading (subleading) photon and $|\eta_{\gamma\gamma}|$ < 2.37. The factors are evaluated using the Powheg NNLOPSevent generator. Uncertainties are taken from PDF variations. QCD scale variations have a negligible impact on these factors. The range of each bin is given in Table 26.

observed statistical correlations between pTyy, Njets, mjj, |DeltaPhijj| and pTj1

ggH default MC + XH predictions

XH ( = VBF + VH + ttH + bbH ) MC predictions

Best-fit values and uncertainties of the production-mode cross sections times branching ratio.

Best-fit values and uncertainties of the simplified template cross sections times branching ratio.

Observed correlations between the measured simplified template cross sections, including both the statistical and systematic uncertainties.

Best-fit values and uncertainties of the simplified template cross sections times branching ratio.

Observed correlations between the measured simplified template cross sections, including both the statistical and systematic uncertainties.

Observed correlations between the measured simplified template cross sections, including both the statistical and systematic uncertainties.

Distribution of the missing transverse momentum $E_{\mathrm{T}}^{\mathrm{miss}}$ for the sample satisfying all requirements of the $\mathrm{SR}^{\gamma\gamma}_{W-L}$ selection except the $E_{\mathrm{T}}^{\mathrm{miss}}$ requirement itself. Overlaid are the expected SM backgrounds, separated into the various contributing sources. Also shown are the signal expectations for the ($m_{\tilde{W}}$, $m_{\tilde{\chi}^{0}_{1}}$) = (1000,100) GeV and ($m_{\tilde{W}}$, $m_{\tilde{\chi}^{0}_{1}}$) = (1000,800) GeV models. The vertical dashed lines and right-pointing arrows show the region of the $E_{\mathrm{T}}^{\mathrm{miss}}$ observable selected for inclusion in $\mathrm{SR}^{\gamma\gamma}_{W-L}$ and $\mathrm{SR}^{\gamma\gamma}_{W-H}$. The lower panels show the ratio of observed data to the combined SM expectation. For these plots, the band represents the range of combined statistical and systematic uncertainty in the SM expectation. Events outside the range of the displayed region are included in the highest-value bin.

Distribution of the missing transverse momentum $E_{\mathrm{T}}^{\mathrm{miss}}$ for the sample satisfying all requirements of the $\mathrm{SR}^{\gamma\gamma}_{W-H}$ selection except the $E_{\mathrm{T}}^{\mathrm{miss}}$ requirement itself. Overlaid are the expected SM backgrounds, separated into the various contributing sources. Also shown are the signal expectations for the ($m_{\tilde{W}}$, $m_{\tilde{\chi}^{0}_{1}}$) = (1000,100) GeV and ($m_{\tilde{W}}$, $m_{\tilde{\chi}^{0}_{1}}$) = (1000,800) GeV models. The vertical dashed lines and right-pointing arrows show the region of the $E_{\mathrm{T}}^{\mathrm{miss}}$ observable selected for inclusion in $\mathrm{SR}^{\gamma\gamma}_{W-L}$ and $\mathrm{SR}^{\gamma\gamma}_{W-H}$. The lower panels show the ratio of observed data to the combined SM expectation. For these plots, the band represents the range of combined statistical and systematic uncertainty in the SM expectation. Events outside the range of the displayed region are included in the highest-value bin.

Comparisons between expected and observed content of the validation and signal regions for the photon+jets analysis. The uncertainties in the expected numbers of events are the combined statistical and systematic uncertainties. The lower panel shows the pull (difference between observed and expected event counts normalized by the uncertainty) for each region.

Distribution of the missing transverse momentum $E_{\mathrm{T}}^{\mathrm{miss}}$ for the sample satisfying all requirements of the $\mathrm{SR}^{\gamma j}_{H}$ selection except the $E_{\mathrm{T}}^{\mathrm{miss}}$ requirement itself. Overlaid are the expected SM backgrounds, separated into the various contributing sources. Also shown are the signal expectations for points in the $m_{\tilde{g}}-m_{\tilde{\chi}^{0}_{1}}$ parameter space of the GGM model relevant to the photon+jets analysis (mass values in GeV). The value of the gluino mass arises from the choice $M_{3}$ = 1900 GeV. The $\tilde{\chi}^{0}_{1}$ mass values of 1868, 1920, 442 and 652 GeV arise from the choices $\mu$ = 1810, 1868, 400 and 600 GeV, respectively, combined with the constraint that the branching fraction of $\tilde{\chi}^{0}_{1}$ $\to \gamma \tilde{G}$ be 50%. The vertical dashed lines and right-pointing arrows show the region of the $E_{\mathrm{T}}^{\mathrm{miss}}$ observable selected for inclusion in $\mathrm{SR}^{\gamma j}_{H}$ and $\mathrm{SR}^{\gamma j}_{L}$ for $\mathrm{SR}^{\gamma j}_{L200}$, the $E_{\mathrm{T}}^{\mathrm{miss}}$ requirement is 200 GeV rather than 300 GeV. The lower panels show the ratio of observed data to the combined SM expectation. For these plots, the band represents the range of statistical uncertainty in the SM expectation. Events outside the range of the displayed region are included in the highest-value bin.

Distribution of the missing transverse momentum $E_{\mathrm{T}}^{\mathrm{miss}}$ for the sample satisfying all requirements of the $\mathrm{SR}^{\gamma j}_{L}$ or $\mathrm{SR}^{\gamma j}_{L200}$ selection except the $E_{\mathrm{T}}^{\mathrm{miss}}$ requirement itself. Overlaid are the expected SM backgrounds, separated into the various contributing sources. Also shown are the signal expectations for points in the $m_{\tilde{g}}-m_{\tilde{\chi}^{0}_{1}}$ parameter space of the GGM model relevant to the photon+jets analysis (mass values in GeV). The value of the gluino mass arises from the choice $M_{3}$ = 1900 GeV. The $\tilde{\chi}^{0}_{1}$ mass values of 1868, 1920, 442 and 652 GeV arise from the choices $\mu$ = 1810, 1868, 400 and 600 GeV, respectively, combined with the constraint that the branching fraction of $\tilde{\chi}^{0}_{1} \to \gamma \tilde{G}$ be 50%. The vertical dashed lines and right-pointing arrows show the region of the $E_{\mathrm{T}}^{\mathrm{miss}}$ observable selected for inclusion in $\mathrm{SR}^{\gamma j}_{H}$ and $\mathrm{SR}^{\gamma j}_{L}$ for $\mathrm{SR}^{\gamma j}_{L200}$, the $E_{\mathrm{T}}^{\mathrm{miss}}$ requirement is 200 GeV rather than 300 GeV. The lower panels show the ratio of observed data to the combined SM expectation. For these plots, the band represents the range of statistical uncertainty in the SM expectation. Events outside the range of the displayed region are included in the highest-value bin.

Expected exclusion limits in the gluino-bino mass plane, using the $\mathrm{SR}^{\gamma\gamma}_{S-H}$ analysis for $m_{\tilde{\chi}^{0}_{1}} > 1600$ GeV and the $\mathrm{SR}^{\gamma\gamma}_{S-L}$ analysis for $m_{\tilde{\chi}^{0}_{1}} < 1600$ GeV.

Observed exclusion limits in the gluino--bino mass plane, using the $\mathrm{SR}^{\gamma\gamma}_{S-H}$ analysis for $m_{\tilde{\chi}^{0}_{1}} > 1600$ GeV and the $\mathrm{SR}^{\gamma\gamma}_{S-L}$ analysis for $m_{\tilde{\chi}^{0}_{1}} < 1600$ GeV.

Expected exclusion limit in the squark-bino mass plane, using the $\mathrm{SR}^{\gamma\gamma}_{S-H}$ analysis for $m_{\tilde{\chi}^{0}_{1}} > 900$ GeV and the $\mathrm{SR}^{\gamma\gamma}_{S-L}$ analysis for $m_{\tilde{\chi}^{0}_{1}} < 900$ GeV.

Observed exclusion limit in the squark--bino mass plane, using the $\mathrm{SR}^{\gamma\gamma}_{S-H}$ analysis for $m_{\tilde{\chi}^{0}_{1}} > 900$ GeV and the $\mathrm{SR}^{\gamma\gamma}_{S-L}$ analysis for $m_{\tilde{\chi}^{0}_{1}} < 900$ GeV.

Expected exclusion limit in the wino-bino mass plane, using the $\mathrm{SR}^{\gamma\gamma}_{W-H}$ analysis for $m_{\tilde{\chi}^{0}_{1}} > 400$ GeV and the $\mathrm{SR}^{\gamma\gamma}_{W-L}$ analysis for $m_{\tilde{\chi}^{0}_{1}}$ < 400$ GeV.

Observed exclusion limit in the wino-bino mass plane, using the $\mathrm{SR}^{\gamma\gamma}_{W-H}$ analysis for $m_{\tilde{\chi}^{0}_{1}} > 400$ GeV and the $\mathrm{SR}^{\gamma\gamma}_{W-L}$ analysis for $m_{\tilde{\chi}^{0}_{1}}$ < 400$ GeV.

Expected exclusion limits for the $\mu > 0$ higgsino-bino GGM model explored by the photon+jets analysis.

Observed exclusion limits for the $\mu > 0$ higgsino-bino GGM model explored by the photon+jets analysis.

Distribution of the transverse momentum $p_{\mathrm{T}} (\ell\gamma\gamma)$ of events in the $\ell\gamma\gamma$ control region (except without a cut on $p_{\mathrm{T}} (\ell\gamma\gamma)$). Also shown is the expected contribution from various SM sources, including $W(\to\ell\nu) + \gamma\gamma$ production itself. The displayed uncertainties are a combination of those from all SM sources except $W(\to\ell\nu) + \gamma\gamma$ production, and include statistical and systematic uncertainties.

Distribution of $E_{\mathrm{T}}^{\mathrm{miss}}$ for diphoton events in a validation region defined by a requirement of $H_{\mathrm{T}} > 1750$ GeV. Also shown is the expected contribution from various SM sources, as well as their combined statistical and systematic uncertainties.

Distribution of $H_{\mathrm{T}}$ for diphoton events in a validation region defined by requirement of $E_{\mathrm{T}}^{\mathrm{miss}} > 100$ GeV. Also shown is the expected contribution from various SM sources, as well as their combined statistical and systematic uncertainties.

Distribution of $m_{\mathrm{eff}}$ for events satisfying all requirements $\mathrm{SR}^{\gamma j}_{H}$ save the $m_{\mathrm{eff}}$ requirement itself. Also shown is the expected contribution from various SM sources, and their combined statistical uncertainties.

Distribution of $m_{\mathrm{eff}}$ for events satisfying all requirements $\mathrm{SR}^{\gamma j}_{L}$ save the $m_{\mathrm{eff}}$ requirement itself. Also shown is the expected contribution from various SM sources, and their combined statistical uncertainties.

Derived exclusion limits for the gluino-bino GGM model explored by the diphoton analysis. For each point in the gluino-bino parameter space, the SR ($\mathrm{SR}^{\gamma\gamma}_{S-L}$ or $\mathrm{SR}^{\gamma\gamma}_{S-H}$) that provides the best expected sensitivity is used to estimate the exclusion likelihood. The model dependent upper limits on cross-section (fb) are shown by grey numbers for each signal point.

Derived exclusion limits for the squark-bino GGM model explored by the diphoton analysis. For each point in the squark-bino parameter space, the SR ($\mathrm{SR}^{\gamma\gamma}_{S-L}$ or $\mathrm{SR}^{\gamma\gamma}_{S-H}$) that provides the best expected sensitivity is used to estimate the exclusion likelihood. The model dependent upper limits on cross-section (fb) are shown by grey numbers for each signal point.

Derived exclusion limits for the wino-bino GGM model explored by the diphoton analysis. For each point in the wino-bino parameter space, the SR ($\mathrm{SR}^{\gamma\gamma}_{W-L}$ or $\mathrm{SR}^{\gamma\gamma}_{W-H}$) that provides the best expected sensitivity is used to estimate the exclusion likelihood. The model dependent upper limits on cross-section (fb) are shown by grey numbers for each signal point.

Derived exclusion limits for the $\mu > 0$ higgsino-bino GGM model explored by the photon+jets analysis. For each point in the higgsino-bino parameter space, the SR ($\mathrm{SR}^{\gamma j}_{L}$ or $\mathrm{SR}^{\gamma j}_{H}$) that provides the best expected sensitivity is used to estimate the exclusion likelihood. The model dependent upper limits on cross-section (fb) are shown by grey numbers for each signal point.

Derived exclusion limits for the gluino-bino GGM model explored by the diphoton analysis. For each point in the gluino-bino parameter space, the SR ($\mathrm{SR}^{\gamma\gamma}_{S-L}$ or $\mathrm{SR}^{\gamma\gamma}_{S-H}$) that provides the best expected sensitivity is used to estimate the exclusion likelihood. The labels indicate the best-expected signal region for each point, where SL and SH mean $\mathrm{SR}^{\gamma\gamma}_{S-L}$ and $\mathrm{SR}^{\gamma\gamma}_{S-H}$, respectively.

Derived exclusion limits for the squark-bino GGM model explored by the diphoton analysis. For each point in the squark-bino parameter space, the SR ($\mathrm{SR}^{\gamma\gamma}_{S-L}$ or $\mathrm{SR}^{\gamma\gamma}_{S-H}$) that provides the best expected sensitivity is used to estimate the exclusion likelihood. The labels indicate the best-expected signal region for each point, where SL and SH mean $\mathrm{SR}^{\gamma\gamma}_{S-L}$ and $\mathrm{SR}^{\gamma\gamma}_{S-H}$, respectively.

Derived exclusion limits for the wino--bino GGM model explored by the diphoton analysis. For each point in the wino-bino parameter space, the SR ($\mathrm{SR}^{\gamma\gamma}_{W-L}$ or $\mathrm{SR}^{\gamma\gamma}_{W-H}$) that provides the best expected sensitivity is used to estimate the exclusion likelihood. The labels indicate the best-expected signal region for each point, where WL and WH mean $\mathrm{SR}^{\gamma\gamma}_{W-L}$ and $\mathrm{SR}^{\gamma\gamma}_{W-H}$, respectively.

Derived exclusion limits for the $\mu > 0$ higgsino-bino GGM model explored by the photon+jets analysis. For each point in the higgsino-bino parameter space, the SR ($\mathrm{SR}^{\gamma j}_{L}$ or $\mathrm{SR}^{\gamma j}_{H}$) that provides the best expected sensitivity is used to estimate the exclusion likelihood. The labels indicate the best-expected signal region for each point, where L and H mean $\mathrm{SR}^{\gamma j}_{L}$ and $\mathrm{SR}^{\gamma j}_{H}$, respectively.

Acceptance and efficiency for $\mathrm{SR}^{\gamma\gamma}_{S-L}$ for the signal models of the gluino-bino GGM grid.

Acceptance and efficiency for $\mathrm{SR}^{\gamma\gamma}_{S-H}$ for the signal models of the gluino-bino GGM grid.